Barriers to cleaning of shared latrines in slums of Addis Ababa, Ethiopia.

Shared latrines and other shared sanitation facilities are vital for communities that lack private latrines. However, the cleanliness of shared latrines continues to be a problem in sub-Saharan Africa, including slums of Addis Ababa, Ethiopia. Investigating the barriers to cleaning of shared latrines may inform the future strengthening of comprehensive sanitation programs in slums of Addis Ababa, Ethiopia. Thus, a community-based unmatched case-control study was conducted among 100 case and 200 control households that were users of shared latrines from September to November 2017 in a slum district in Addis Ababa. Cases were those who had not cleaned their shared latrines and controls were those who had cleaned their shared latrines at least once during the week prior to data collection. Data were collected using a structured questionnaire and an on-the-spot-observational checklist and analyzed using bivariate (crude odds ratio [COD]) and multivariable (adjusted odds ratio [AOR]) unconditional logistic regression model. Variables having a p-value of less than 0.25 from the bivariate logistic regression analysis were retained into multivariable analysis. From the multivariable analysis, variables with p<0.05 were declared as factors significantly associated with barriers to cleaning of shared latrines. We found that about half 99 (49.5%) of shared latrines used by cases and almost one-third 32 (32.0%) of the shared latrines used by controls had visible cracks and spaces in the floor and slabs. The barriers to cleaning of shared latrines were found to be monthly household income of less than $55.60 USD (AOR = 1.80; 95%CI: 1.2-3.10), users feeling a lack of privacy during latrine use (AOR = 2.95; 95% CI: 1.60-5.43), no locking latch on the latrine door (AOR = 4.60; 95% CI: 2.43-8.79), inadequate ventilation of latrine (AOR: 4.88; 95% CI: 2.44-9.63), lack of regular monitoring of latrine by health extension workers (AOR = 2.86; 95%CI: 1.32-6.21) and a lack of enough water at home for cleaning the latrine (AOR = 4.91; 95% CI: 1.07-9.48). This study found several barriers to cleaning of shared latrines in slums of Addis Ababa. We recommend that stakeholders promote cleaning of shared latrines by designing programs to improve latrine privacy by adding or modifying the superstructure and including a door with locking latch, to make adjustments to the structure for better ventilation, to ensure regular monitoring of latrines by health extension workers and to make enough water consistently available for regular latrine cleaning.

Background

Rapid expansion of urbanization in developing countries has resulted the creation of urban slums [1, 2], which are characterized by one or more of the features of overcrowding, inadequate safe water supply, insecure property tenure, inadequate drainage and sewage networks, and lack of sanitation or proper solid waste disposal [2-6].

Shared latrines, including public latrines, are common in African slums, while a lack of space for construction of private latrines is a big challenge [1, 5, 7]. During the rainy season experienced by many African countries when unsealed shared latrines in slums may overflow and disperse pathogens [8] and diarrhea incidence in slums tends to peak [9], higher diarrhea transmission occurs among children under five than during the dry seasons. Furthermore, lack of cleaning of shared latrines in slums worsens the already bad sanitation situation [10].

Heijenen et al. reported that shared latrines were generally in poorer condition than those latrines that were not shared [11, 12]. A shared latrine can be equated with a common good whose management depends on the users. If users do not work together towards keeping the facilities clean, the quality and utilization of the latrine may decline [13].

In Africa’s urban slums where private latrines are lacking, there is a great demand for public latrines. Therefore, improving their hygienic status is vital for minimizing disease outbreaks in these areas [3]. Bartlett (2003) found that the lack of latrines in poor communities caused many people to defecate in the open or into plastic bags and papers that were then discarded with the household garbage [14]. A recent study in eastern Ethiopia found a lack of effective social mobilization to be the main cause for open defecation [15].

Addis Ababa is an Ethiopian example of a city characterized by overcrowded settlements with shared latrines that are in poor hygienic condition [16, 17]. This situation increases the risk of diarrheal and other diseases [18, 19]. For example, in 2008, the city-wide data on basic indicators in Addis Ababa reported that 26.0% of the houses and the majority of slum dwellers had no toilet facility, 33.0% of households shared a latrine among more than six households and 71.0% of the households did not have adequate sanitation [16]. Furthermore, studies in slums of Addis Ababa indicated that poorly maintained shared latrines may have contributed to contamination of household water supplies as a result of the proximity of many latrines to crowded neighborhoods [19, 20].

The WHO/UNICEF Joint Monitoring Program (JMP) excludes what it calls ‘shared’ sanitation facilities—those used by two or more households—from the definition of ‘improved sanitation’ due to the concern that shared toilets tend to be less hygienic than private ones [21]. However, there is limited existing information on why shared latrines are not cleaned by users in slum contexts. A previous study done in slums of Addis Ababa found that sanitation and hygienic levels of shared latrines were low, although the main reasons for this could not be addressed [19]. Therefore, the purpose of this study was to address this gap in knowledge by identifying factors significantly associated with barriers to cleaning of shared latrines in slums of Addis Ababa, Ethiopia. To that end, this unmatched case–control study was conducted using data collected by on-the-spot-observation and interviews of study participants who reported being primarily responsible for cleaning of the shared latrines.

Method

Description of the study area

The study was conducted in District 05 in Lideta Sub-City, Addis Ababa. Addis Ababa has 116 districts (the lowest administrative unit in Addis Ababa). In the absence of a clear demarcation of the slums in Addis Ababa, the UN-HABITAT study in 2010 estimated that four-fifths (80%) of Addis Ababa was a slum, where most residents lived in houses rented from the local government [17]. A previous study in slums of Addis Ababa reported that 51.0% of slum residents used public latrines and 26.8% of them also used pit latrines that were without a slab floor [19]. This study was conducted among shared latrine users, which included users of public latrines. Shared latrines were those that were shared by two or more households.

Study design and study period

A community-based unmatched case–control study was conducted from September to November, 2017. Cases were those who had not cleaned a shared latrine and controls were those who had cleaned a shared latrine at least once during the week prior to data collection based on self-report. Case participants and control participants did not share the same latrines.

Source populations, inclusion and exclusion criteria

The source population was all dwellers in District 05 in Lideta Sub-City, Addis Ababa who had used shared latrines during the week prior to data collection, whereas the study population was selected cases and controls among District 05 residents in Lideta Sub-City who had used shared latrines during the week prior to data collection. In this study, latrine users who were responsible for the cleaning of their latrines were included, whereas latrine users who were not responsible for the cleaning of their latrines were excluded. Households that had private latrines and did not share with others were excluded.

Sample size determination

The sample size was determined using Epi Info version 7.0 with the consideration of proportion (p) of households that had not cleaned a shared latrine in the one week prior to data collection taken as 50.0% due to lack of studies in a similar setting, and expected odds ratio of 1.5 used based on another study suggestion to obtain adequate sample size [22]. Furthermore, power of 80.0% and control-to-case ratio of 2:1 was also used in line with the Pitman Efficiency assumption [23]. Considering a 10% non-response rate, the final adequate sample size becomes 100 cases and 200 controls, for a total of 300 households of users of shared latrines.

Case and control study participant recruitment

By house-to-house visits, cases were selected from those who had not cleaned the shared latrine at least once during the week prior to data collection and controls were selected from shared latrine users who had cleaned the latrine at least once during the week prior to data collection. The selection of study participant cases and controls was performed randomly after the participants self-reported that either they had cleaned (controls) or not cleaned (cases) the shared latrine.

Study participants who were not available during the survey were revisited once on the same day or the next day. If not available again, a third visit was made. If not available the third time, the study participant would have been considered a non-respondent. However, in this study there was no non-respondent, which might be due to the random selection of cases and controls based on the self-report of latrine cleaning condition (cleaned or not cleaned), before the sample size was achieved. Since most of the slum dwellers were day laborers and the study area was business areas, the data was collected every weekend on Saturdays at mid-day and Sunday afternoons, times when individuals were more likely to be at home and available to participate in the survey.

Operational definitions

Slums: Areas dominated by informal settlement that are characterized by one or more of the five characteristics of overcrowding, poor sanitation, insecure land tenure, lack of access to water supply, poor housing quality and other infrastructure [2].

Shared latrines: Refers to latrines shared by two or more households, including public latrines that are used by known households with a shared responsibility for cleaning by the users, whereas public latrines publicly accessible for everyone at a market, school or main road were excluded from this study.

Latrine access: Means that individuals accessed only the latrines that were within a certain distance from their homes as provided by kebeles for shared use, or use of their own shared latrine, or use of a latrine that was part of a household and also shared by two or more households.

Barriers to cleaning of shared latrines: Obstacles that prevented users from cleaning shared latrines.

Cases: Users of shared latrines who self-reported that they had not cleaned the latrine during the week prior to data collection.

Controls: Users of shared latrines who self-reported that they had cleaned the latrine at least once during the week prior to data collection.

Data collection by observation and interview

Household survey data were collected using a pre-tested questionnaire and an observational checklist. The questionnaire and the observational checklist were adapted from various published literature [3, 24–28] and WHO and UN-HABITAT reports [1, 16, 29, 30]. The survey tool was first prepared in English (SI) and then translated into (local language) Amharic (SII) for use by participating households. Three data collectors who were BSc professionals in environmental health administered the survey. Data collectors were trained by the principal investigator for two days on the aim of the study, the content of the questionnaire and observation checklist, ethical issues and approaches during data collection.

Variables measured by interview included age, sex, marital status, educational status, occupation, monthly household income, household size, number of rooms in the house, number of households sharing latrine, privacy status during use of shared latrine, presence or absence of users participating collectively in decision making, presence or absence of monitoring of the latrines by health extension workers, latrine considered to be clean or not by users and availability of water at home for cleaning the latrine.

To collect data by direct observation, study participants were asked to show their latrine to the data collector. Data measured by on-the-spot-observation included superstructure materials, presence or absence of latrine door, locking latch and slab, status of latrine pit fullness, condition of slab (cracked and/or broken), ventilation condition of latrine, availability of handwashing facilities inside and/or near the latrine, presence of water in the handwashing facilities, availability of soap near the handwashing facilities.

Daily supervision was carried out by one supervisor and the principal investigator to check the completeness of the questionnaires and consistency of the data. When there was any missing data, correction was made by re-visiting the participant during the same day or the next day.

Data quality assurance

To ensure the quality of the data, we also pre-tested the questionnaire among 10 cases and 20 control households (10% of the sample size) in one non-selected area of District 4 in Lideta Sub-City to evaluate its face and content validity. During the pre-test, face validity was verified by checking that the questions measured what they were intended to measure. Content validity was also checked by three environmental health professionals who evaluated whether the survey contained questions that covered all aspects of the contents being measured. Data collection began after we approved the face and content validity of the survey tool.

Any amendment made to the questionnaire such as elimination of unnecessary questions, revision of confusing terms, and addition of important questions was based on the pre-test. Inter-observer reliability was ensured by providing clear definitions during training about shared latrines, cases and controls, latrine cleaning, superstructure of the latrine and events to be recorded and by providing feedback about discrepancies during daily supervision.

Also, 10% of the study participants were re-interviewed by another interviewer to check reliability of the information collected by different interviewers. The qualifications of the interviewers and the training they received also reduced the likelihood that interviewer bias occurred. Entered data was re-entered on 10.0% of the sample to check consistency and reduce errors of data entry. After the data was entered and cleaned, quality assurance measures were employed using descriptive statistics from cross-tabulation and frequency distribution before performing statistical analysis.

Data management and analysis

The collected data were coded and entered in to EpiData version 3.1 and exported to Statistical Package for the Social Sciences (SPSS) version 23.0 for cleaning and analysis. Descriptive statistics were carried out, including means ±SD (standard deviations) for continuous variables. The presence of multi-collinearity among independent variables was checked using variance inflation factor (VIF). We found a maximum VIF of 2.0, which indicated there was no multi-collinearity between independent variables.

Unconditional logistic regression model was used for data analysis. The modeling strategy involved estimating the bivariate analysis (crude odds ratio [COR]) and multivariable analysis (adjusted odds ratio [AOR]) at 95% CI. For selection to the final model, variables with a p-value less than 0.25 from bivariate analysis were included to the multivariable analysis. From the adjusted analysis, variables with p < 0.05 were taken as statistically significant and independently associated with barriers to cleaning of shared latrines in slums of Addis Ababa. The goodness-of-fit of the model was checked using the Hosmer-Lemeshow statistic [31], finding a p-value of 0.937, indicated the model was fit.

Ethical considerations

Ethical clearance was obtained from the Institutional Review Board (IRB) of GAMBY Medical and Business College, Addis Ababa, Ethiopia. Permission to undertake this study was also obtained from Addis Ababa Health Bureau, slum District 05 in Lideta Sub-City. Written consent was obtained during recruitment of the study participants. During data collection, study participants who were using unclean latrines were advised to keep their latrine in a hygienic condition. Study participants also were informed that participation was affirmed by the procedure of probability sampling technique which provides an equal chance of selection. Confidentiality of the study was maintained by establishing codes instead of using names.

Results

Socio-demographic and economic characteristics of case and control households

This study included 300 study participants (100 cases and 200 controls) and had a response rate of 100%. Of the study participants, 49 (49.0%) of cases and 88 (44.0%) of controls were males. The educational level of almost half 48 (48.0%) of cases and two-thirds 130 (65.0%) of controls were illiterate. The average monthly household income was $55.60 USD (United States Dollars); and 27 (27.0%) of cases and 89 (44.5%) of controls had less than $55.60 USD monthly household income. Of all households, about (two-thirds, 133 (66.0%) controls and 63 (63.0%) cases, rented government houses administered by kebeles (Table 1).

Table 1

Socio-demographic and economic characteristics among case and control study participants in slums of District 05, Lideta Sub-City, Addis Ababa, Ethiopia.

Variable	Category	Case (N = 100)	Control (N = 200)	COR (95% CI)
		n(%)	n(%)
Age (years)	25–34	23(23.0)	52(26.0)	0.7(0.4–1.4)
	35–44	34(34.0)	73(36.5)	0.8(0.5–1.4)
	>44	43(43.0)	75(37.5)	Ref
Sex	Male	49(49.0)	88(44.0)	0.8(0.5–1.3)
	Female	51(51.0)	112(56.0)	Ref
Marital status	Married	76(76.0)	152(76.0)	1.6(0.8–3.5)
	Single	15(15.0)	18(9.0)	0.5(0.2–1.3)
	Widowed	5(5.0)	21(10.5)	0.9(0.3–3.0)
	Divorced	4(4.0)	9(4.5)	Ref
Educational status	Illiterate	48(48.0)	130(65.0)	0.3(0.1–1.1)
	Read and write	22(22.0)	47(23.5)	0.4(0.1–1.4)
	Elementary	24(24.0)	18(9.0)	1.1(0.3–4.2)
	Secondary or above	6(6.0)	5(2.5)	Ref
Occupation	Housewife	44(44.0)	90(45.0)	0.9(0.4–2.0)
	Government employee	33(33.0)	59(29.5)	1.1(0.4–2.3)
	Daily laborer	12(12.0)	31(15.5)	0.7(0.3–1.9)
	Merchant	11(11.0)	20(10.0)	Ref
Monthly household income ($US)	Less than $55.60 US	27(27.0)	89(44.5)	2.2(1.3–3.6)
	$55.60 US or more	73(73.0)	111(55.5)	Ref
Household size (persons)	6 or more persons	24(24.0)	43(21.5)	1.1(0.6–2.0)
	1–5 persons	76(76.0)	157(78.5)	Ref
House ownership	Rented from government (kebele)	63(63.0)	133(66.5)	1.1(0.6–0.2)
	Privately rented	21(21.0)	40(20.0)	1.2(0.6–2.5)
	Owned by householder	16(16.0)	27(13.5)	Ref
Number of rooms in house	≤2	60(60.0)	144(72.0)	1.7(1.1–2.8)
	>2	40(40.0)	56(28.0)	Ref

1, Reference category; COR, Crude odds ratio

*The average exchange rate for $1 USD was 20.0 birr from September to November 2017.

The superstructure and privacy-related characteristics of the shared latrines among cases and controls

About two-thirds 62 (62.0%) cases and 143 (71.5%) controls shared one latrine among 11 to 13 households, whereas 23 (23.0%) cases and 37 (18.5%) controls shared one latrine among 6 to 10 households. About one-third 30 (30.0%) of case household latrines and one-fifth 43 (21.5%) of control household latrines had a superstructure constructed with bricks or stones. About one-tenth 13 (13.0%) of the case households and more than half 107 (53.7%) of controls shared latrines that had no door. Two-thirds 67 (67.0%) of cases and three-fourths 157 (78.5%) of controls mentioned lack of privacy when using the latrine was a problem (Table 2).

Table 2

Superstructure and privacy-related characteristics of shared latrines among case and control study participants in slums of District 05, Lideta Sub-City, Addis Ababa, Ethiopia.

		Case (N = 100)	Control (N = 200)	COR (95%CI)
Characteristics	Category	n(%)	n(%)
Number of households sharing latrine	≤5	15(15.0)	20(10.0)	Ref
	6–10	23(23.0)	37(18.5)	0.8(0.4–1.9)
	11–13	62(62.0)	143(71.5)	0.6(0.3–1.2)
Superstructure materials of shared latrine	Bricks/stone	30(30.0)	43(21.5)	1.1(0.60–2.1)
	Mud/wood	5(5.0)	41(20.5)	0.9(0.15–2.0)
	Corrugated iron sheets	65(65.0)	121(58.0)	Ref
Adequate privacy during use of shared latrine	No	33(33.0)	157(78.5)	7.4(4.3–12.6)
	Yes	67(67.0)	43(21.5)	Ref
Shared latrine had a door	No	13(13.0)	107(53.7)	7.7(4.0–14.7)
	Yes	87(87.0)	93(46.5)	Ref
Shared latrine had door with a locking latch	No	23(23.0)	136(68.0)	7.1(4.1–12.3)
	Yes	77(77.0)	64(32.0)	Ref
Shared latrine had good ventilation	No	21(21.0)	143(71.5)	9.4(5.3–16.7)
	Yes	79(79.0)	57(28.5)	Ref

Shared latrine slab characteristics, latrine monitoring and collective decision-making practices

About 32 (32.0%) of the case households’ latrines and nearly half of control households’ 99 (49.5%) latrines had cracked or broken slabs. Almost two-thirds 121 (60.5%) of control households and half 53 (53.0%) of case households reported conflicts among latrine users. One-quarter 26 (26.0%) of case and four-fifths 166 (83.0%) of control households’ latrines were not monitored regularly by health extension workers. Most control households 174 (87.0%), but only 31 (31.0%) of the case households, considered their latrines not clean (Table 3).

Table 3

Latrine slab, monitoring practices and other characteristics of shared latrines among case and control study participants in slums of District 05, Lideta Sub-City, Addis Ababa, Ethiopia.

Characteristics	Category	Case (N = 100)	Control (N = 200)	COR (95%CI)
		n(%)	n(%)
Cracked or broken slab	No	68(68.0)	101(50.5)	2.1(1.3–3.4)
	Yes	32(32.0)	99(49.5)	Ref
The latrine pit was full	No	75(75.0)	129(64.5)	0.6(0.3–1.0)
	Yes	25(25.0)	71(35.5)	Ref
Users participated collectively in decision making	No	23(23.0)	147(73.5)	9.3(5.3–16.3)
	Yes	77(77.0)	53(26.5)	Ref
Users experienced conflict	Yes	53(53.0)	121(60.5)	1.4(0.8–2.2)
	No	47(47.0)	79(39.5)	Ref
Regular monitoring of the latrines by health extension workers	No	26(26.0)	166(83.0)	13.9(7.8–24.8)
	Yes	74(74.0)	34(17.0)	Ref
Latrine was considered to be clean by users	Yes	69(69.0)	26(13.0)	14.9(8.2–26.9)
	No	31(31.0)	174(87.0)	Ref

Ref, Reference category.

Availability of water and handwashing facilities in the shared latrines

Nearly one-third 31 (31.0%) of control household had enough water available within or near the latrine for cleaning the sanitation facilities. A large majority of case 84 (84.0%) and control 165 (82.5%) latrines had no handwashing facilities inside and/or near the latrine. Of those case households’ latrines that had handwashing facilities inside and/or near the latrine 16 (16.0%), only 4 (25.0%) had water and 2 (12.5%) had water and soap (Table 4).

Table 4

Availability of water and handwashing facilities in shared latrines among case and control study participants in slums of District 05 in Lideta Sub-City, Addis Ababa, Ethiopia.

Variables	Category	Case (N = 100)	Control (N = 200)	COR (95%CI)
		n(%)	n(%)
Enough water was available at home for cleaning the latrine¥	No	69(69.0)	194(97.0)	0.7(0.8–6.3)
	Yes	31(31.0)	6(3.0)	Ref
Handwashing facilities inside and/or near the latrine*	No	84(84.0)	165(82.5)	1.1(0.7–2.5)
	Yes	16(16.0)	35(17.5)	Ref
Presence of water in the handwashing facilities*	No	12(75.0)	27(77.1)	0.8(0.9–1.7)
	Yes	4(25.0)	8(22.9)	Ref
Availability of soap near the handwashing facilities*	No	14(87.5)	30(85.7)	1.16(0.8–1.2)
	Yes	2(12.5)	5(14.3)	Ref

Ref, Reference category.

*Not included during the logistic regression analysis due to the presence of zero frequency either in the case or control households.

¥The quantity of the available water was not measured and only the perception that they have enough water at home for latrine cleaning was studied.

Barriers associated with not cleaning shared latrines

This study identified six barriers significantly associated with not cleaning shared latrines in slums of District 05 in Lideta Sub-City, Addis Ababa. Householders that had a monthly income of less than $55.60 USD were 1.80 times (AOR = 1.80; 95% CI: 1.2–3.10) higher not to cleaned the shared latrine the previous week than those that had a monthly income of $55.60 USD or above. The odds developing not to cleaned latrines among shared latrine users who felt a lack of privacy when using the latrines were 2.95 times (AOR = 2.95; 95% CI: 1.60–5.43) higher than those who had a feeling of privacy during use. The odds of developing not to cleaned the shared latrines among users of shared latrines without a locking latch for the latrines were 4.6 times (AOR = 4.60; 95% CI: 2.43–8.79) higher compared to those users of a shared latrine that had a locking latch.

The odds of developing not to cleaned shared latrines among householders using shared latrines that were without adequate ventilation were 4.88 times (AOR: 4.88; 95% CI: 2.44–9.63) higher than those who used a shared latrine that had adequate ventilation. The odds of developing not to cleaned shared latrines among users of shared latrines not monitored regularly by health extension workers were 2.86 times (AOR = 2.86; 95% CI: 1.32–6.21) higher than those using shared latrines that were monitored by health extension workers. The odds of developing not to cleaned shared latrines among users who believed that there was not enough water at home to clean the latrine were 4.91 times (AOR = 4.91; 95% CI: 1.07–9.48) higher than those who believed there was enough water at home to clean the latrine (Table 5).

Table 5

Barriers associated with cleaning of shared latrines from multivariable logistic regression analysis in slums of District 05, Lideta Sub-City, Addis Ababa, Ethiopia.

Variables	Category	Cases (N = 100)	Controls (N = 200)	AOR (95%CI)
		n(%)	n(%)
Household monthly income (USD)	Less than $55.60	27(27.0)	89(44.5)	1.80(1.20–3.10)
	$55.60 or more	73(73.0)	111(55.5)	Ref
Feeling of privacy when using latrine	No	33(33.0)	157(78.5)	2.95(1.60–5.43)
	Yes	67(67.0)	43(21.5)	Ref
Latrine door had a locking latch	No	23(23.0)	136(68.0)	4.60(2.43–8.79)
	Yes	77(77.0)	64(32.0)	Ref
Latrine had adequate ventilation	No	21(21.0)	143(71.5)	4.88(2.44–9.63)
	Yes	79(79.0)	57(28.5)	Ref
Regular monitoring of the latrine by health extension workers¥	No	26(26.0)	166(83.0)	2.86(1.32–6.21)
	Yes	74(74.0)	34(17.0)	Ref
Enough water was available at home for cleaning the latrine*	No	69(69.0)	194(97.0)	4.91(1.07–9.48)
	Yes	31(31.0)	6(3.0)	Ref

Ref, Reference category.

¥ Monitoring by health extension workers (HEWs) were done by regular visit to the latrine and feedback provided to users about keeping the latrine clean.

Discussion

The main aim of this study was to determine the barriers to cleaning of shared latrines in slums of District 05, Lideta Sub-City of Addis Ababa, Ethiopia. This unmatched case–control study found that the barriers to cleaning of shared latrines were monthly household income, users feeling a lack of privacy during latrine use, a shared latrine without locking latch, shared latrine without adequate ventilation, shared latrine not regularly monitored by health extension workers and a lack of enough water at home for cleaning the latrine.

Our findings showed an average household monthly income of less than $55.60 USD was inversely related to cleaning of shared latrines. This might be due to slum residents, who are commonly poor, giving attention to their food security concern rather than the hygienic conditions of shared latrines. A previous study in slums of Addis Ababa found nearly 14.1% of the wealthiest households had access to an improved latrine (not shared) compared to only 0.5% of the poorest who had their own unshared latrine [18]. Furthermore, due to a lack of income, the affordability of latrine cleaning agents might also be a challenge for slum dwellers. Low income status may hinder the purchase of latrine-cleaning and handwashing agents [32].

A lack of privacy was one of the barriers to cleaning of the shared latrines, which might be attributed to the structure being built of poor materials that provided less privacy. A study in Nepal reported that a lack of privacy when using the latrine pushed women to look for open defecation places [33]. Therefore, privacy is an important factor for both latrine use and cleaning. Lack of privacy might be due to the poor cleanliness of the latrine. A study in Kisumu, Kenya that found that latrines constructed with iron sheets, which were likely to have a wooden slab, tended to be more dirty than facilities built of bricks and having a cement floor [28]. The shared latrine without locking latch was also associated with a lack of latrine cleaning in our study, in contrast with the finding of a study in Tanzania that revealed non-shared latrines were less likely to have lockable doors than shared latrines [34]. The presence of a locking latch may increase the sense of ownership among those sharing the latrine. If the shared latrine users have their own keys, others will not use it.

A study in the Kibera slums in Nairobi found that respondents used shared latrines due to the scarcity of private household latrines and the poor condition of other sanitation facilities in that crowded area [35]. Consistent with our findings, Heijenen et al. reported that households sharing sanitation facilities were generally poorer than those that did not share, not necessarily because of sharing sanitation facilities but because of poverty [36]. A study in slums of Uganda showed that 68% of the shared latrines were observed to be significantly dirty [25]. Another study has revealed that shared sanitation facility users are not committed to cleaning shared latrines [26]. In our study, a latrine door having no locking latch was one of the barriers to latrine cleaning, since that allowed it be used by people other than the specified users; this, in turn, may compromise the hygiene of the latrine.

Disposal of garbage close to homes was a significant risk factor for high fly densities and the presence of flies around the shared latrines [37]. A similar study in Rajshahi City slums in Bangladesh revealed that feces were observed around 61.0% of the latrines [38]. Unsanitary condition of latrines and poor hygiene behavior were related to increased diarrhea episodes in slums of An-Nasr in Jordan, Tebbaneh in Libya [39] and Ikare-Akoko in Nigeria [40]. Findings that substandard latrine construction contributed to the presence of flies indicate that improved superstructures may decrease fly densities around latrines [41, 42].

Our findings showed that a lack of regular monitoring of the latrine by health extension workers was a barrier to latrine cleaning, which might be due to the fact that when there is monitoring, users are concerned about implementing the country’s health extension programs, which includes water, sanitation and hygiene programs. Other studies have also showed that the presence of a health extension program in Ethiopia changed the performance of health systems [43, 44]. The findings of our study and previous studies in Ethiopia have consistently shown that the benefit of a health extension program is immense and that consistent follow-up by health extension workers is associated with improvement of the hygienic and sanitation condition of latrines. The frequency of such latrine visits depends on the observed cleanliness of the latrine. For households that maintain clean latrines, the frequency of visits is low, whereas repeated visits can be made to households that do not clean the latrine regularly.

This study also indicates that a lack of water availability is one of the barriers to cleaning shared latrines. In our study setting, the source of the water for all households was the government. However, due to the presence of water supply interruptions [20], the availability of water at home varied and depended on whether a household stored water or not. Some households may also purchase water to cope with problems encountered during a water interruption. Lack of available water at home is not only a barrier to latrine cleaning, but also may be a cause of diarrheal disease among slum-living children under five [20]. For instance, the 2017 WHO/UNICEF Joint Monitoring Program (JMP) report indicated that in 2015, 29.0% of the global population (2.1 billion people) lacked properly managed drinking water services and 61.0% (4.5 billion people) lacked adequate sanitation services [30], which compromises latrine cleaning practices. A study in Tanzania showed water scarcity was a barrier to a national sanitation campaign [45].

Limitations of the study

One of the limitations of this study was that the unmatched case–control study design did not control confounders at the design stage, whereas a matched case–control design may provide better evidence due to the ability to control potential confounders at the design stage. The self-reported data may have bias by underestimating or overestimating the sanitation and hygiene status of the latrine [46], although most of the data was collected by data collectors using an observational checklist. A follow-up study designed with a mixed method of data (quantitative and qualitative) may help to capture more of the practical situation.

Conclusion

We found that the barriers to cleaning a shared latrine were monthly household income, users feeling a lack of privacy during latrine use, lack of a locking latch on the shared latrine door, inadequate latrine ventilation, a lack of regular monitoring of a shared latrine by a health extension worker and a lack of enough water at home for cleaning the latrine.

We recommend that the Addis Ababa Water and Sewerage Authority and other concerned bodies implement the Urban Sanitation Strategic Plan in a well-organized and integrated manner that gives special attention to needs of the shared latrine users in slums of Addis Ababa. Promoting the cleaning of shared latrines through designing strategies for increasing the household monthly income by means of the Urban Productive Safety Net program, increasing the privacy of the latrines by fixing the superstructure, providing latrines with doors and locking latches, adjusting the latrines to allow adequate ventilation, regular monitoring of the latrines by health extension workers and by making enough water available for regular latrine cleaning. Previous findings also have shown that sanitation issues affecting all community members can be addressed in meetings that ensure collective decision making and formulation of rules for sanitation facilities [47].

Survey tool in English language.

(DOCX)

Click here for additional data file.

Survey tool in Amharic (local) language.

(DOCX)

Click here for additional data file.

(DTA)

Click here for additional data file.

7 Sep 2020

Submitted filename: Manuscript with track changes.docx

Click here for additional data file.

12 Oct 2020

PONE-D-20-23172

Barriers to Cleaning of Shared Latrines in Addis Ababa Slums: Unconditional Logistic Regression Analysis

PLOS ONE

Dear Dr. Adane (PhD),

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Nov 15 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Hans-Uwe Dahms, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please clarify the relationshop between the authors and the IRB. We typically expect at least one author to be affiliated with the institution which provides ethical oversight.

3. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services.  If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

The name of the colleague or the details of the professional service that edited your manuscript

A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

4. Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses.

For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information.

5. Please amend either the title on the online submission form (via Edit Submission) or the title in the manuscript so that they are identical.

6. We note that Figure 1 in your submission contains map images which may be copyrighted.

All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (a) present written permission from the copyright holder to publish these figure specifically under the CC BY 4.0 license, or (b) remove the figure from your submission:

a. You may seek permission from the original copyright holder of Figure 1 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b. If you are unable to obtain permission from the original copyright holder to publish these figure under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

Additional Editor Comments:

Pls. consider and REVISE your MS particularly following REVIEWER 1 who otherwise rejected your contribution!

This study uses an unmatched case-control design to assess barriers to cleaning of community latrines in Addis Ababa. Cases were those who did not clean latrines, and controls were those who did clean latrines based on self-report. Overall more information is required around how/why certain variables were selected for use in the logistic regression models (why demographic variables such as gender were not included) as well as details around recruitment methods. Finally, there is some confusion around the differences between data that were collected by observation compared to data collected in surveys, throughout the manuscript. Ideally these data should be reported an analyzed separately to reduce this confusion. My specific comments on each section of the manuscript are included below:

Background

In general, I find the Background section to be a bit too lengthy and I think that some content can be removed or shortened.

The final paragraph should include a succinct description of the study’s purpose (lines 126-127) which includes the study design and data used.

Line 70-71: “Shared facilities can reduce stress when proper maintenance and management systems are in place.” Please define what is meant by “stress” in this context.

Line 96-96: “Strina et al. found that people in latrine-owning 97 households in Salvador, Brazil behaved more hygienically than those without latrine.” Is this study looking at household latrines or shared latrines? This difference is very important to the underlying purpose of the manuscript, please be explicit.

Line 105-107: “Improving cleaning practices of shared latrines is a step toward achieving the United Nations’ 2030 goals for Sustainable Development, in line with achieving Target 6.2 of the Sustainable Development Goal (SDG) of universal access to sanitation as a key priority [29].” I think it may be useful to write out the exact wording of the Target and discuss how it does or does not apply to shared latrines.

Methods

Include a description around how study participants were recruited from the source population. How was the study introduced during the house-to-house visits, was there an IRB process?

How many individuals were considered non-respondents (line 173)?

Please describe what is meant by “regular monitoring by health extension workers”? Who is in charge of this monitoring and who determines which latrines are monitored?

In the paragraph beginning on line 225, please further explain how “validity” was assessed. Was it based on qualitative measurements? Provide more detail here.

In the description of the statistical analysis, explain how covariates were selected for the multivariable analysis. Why were certain questions included on the survey and in the model? Were there any survey questions that were not included in the final adjusted models?

The authors note that they assess multi-collinearity using standard errors, although this is not the correct method. The authors should calculate the variance inflation factor (VIF) and report those values.

Results

Line 316: explain why the cut-off income was $55.60, how was that value chosen?

Table 1: why is “divorced” the reference group in the logistic regression? The reference group is typically one of the more common groups, e.g., married or single. Same comment applies for the referent group select from the educational status and occupation variables.

Why is the “household size” variable entered as a binary variable rather than a continuous number of individuals per household measure?

Because you note that individuals in both the case and control group may be using the same latrines, I think what the survey is measuring is latrine perceptions rather than actual latrines data. For example, there were significant differences between cases and controls in reporting on privacy and whether the latrine had a door. If they are using the same latrines than this difference is based on their perceptions rather than actuality as there would be no difference there.

Do men and women use the same latrines? If not, analyses should be stratified by male/female respondent as they would be assessing a different set of latrines.

It is unclear throughout which data were collected in the surveys with participants and which data were collected using the observational checklist. This leads to a lot of confusion around whether you are talking about the latrine itself or individuals’ perceptions. These sets of data should have different samples sizes and should be reported and analyzed separately.

Discussion

Line 388 “This study used an unmatched case-control design and controlling of the confounders at the design stage was not possible.” Why was this not possible in this context? Also, why were no confounders (gender, age, etc) assessed during the analytic stage?

Finally, the manuscript included several grammatic mistakes throughout which should be addressed. For example:

- In Abstract: “barriers to keeping shared latrines cleaning”

- Line 138-139: “80% of Addis Ababa was slums”

- Line 371: “not regularly monitoring of the latrine”

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors investigated the barriers to cleaning shared latrines in Addis Ababa, Ethiopia. The authors conducted a rigorous household survey and attempt to explain their findings in the manuscript. I commend the authors for the substantial improvements to the manuscript. In particular, the manuscript is substantially improved in its engagement with the broader literature and the writing is improved. As with the previous manuscript, the study appears well designed and the data sound, but I still find the manuscript unsuitable for publication in its current form. Another round of substantial revisions are needed. The manuscript is very repetitive, there are too many details in the abstract, the writing unclear at certain points, there are numerous grammatical mistakes, the statistical analysis is incomplete and unclear, there is little discussion on the limitations, and the some of the recommendations are generic. Further, I would suggest you make use of the supplemental information to make the manuscript more concise.

Main Comments

1. There are too many details in the abstract. Line 30-37 is too much detail. Line 46-50 is a repetition of the previous sentence.

2. Line 35. Here and throughout you never mention what covariates you used in your adjusted analysis

3. Line 50-54: These recommendations are too generic. This manuscript offers an opportunity to make credible suggestions to an interested audience. Increasing household income is a noble aim but is not a feasible recommendation from this data.

4. The introduction is insufficiently focused and should not be a mini-review of the broader field.

5. Line 145: How were study participants selected? Was it every member of District 05 (line 152)? This is unclear to me.

6. Again on Line 168. Did you visit every household?

7. Lines 218-223: Is this the only data that you collected? Or are you only reporting the statistically significant data? It seems like you ran a lot of models, and to avoid accusations of p-hacking, you should adjust your analysis for multiple comparisons.

8. Line 253. This citation is not sufficient here. You need to explain what covariates you used in your adjusted models.

9. Line 316: You calculated odds ratios, not risk ratios. Please make sure the language you use accurately explains your results. As written, this is incorrect.

10. You calculated odds ratios, which are a measure of association, not causation. The discussion section needs to reflect this.

11. Line 334: All the associations you observed could be explain by poverty. If you did not adequately adjust for household wealth or income in your analysis, these finding may be spurious.

12. Line 388: Further discussion of the limitations of this study are needed. What potential sources of bias may have influenced your results?

13. The language in the conclusion needs to better reflect that you found associations, not causation

14. This manuscript may be more suited for a more specialized journal, such as the Journal of Water, Sanitation, and Hygiene for Development

Minor Comments

1. Line 25: As currently written, you are implying there currently is a comprehensive sanitation program in this setting? Is that true?

2. Line 42-46. Why do you use 1 significant figure for some values and 2 significant figures for others?

3. Line 65: All countries are developing. I would suggest you refer to these countries as low- and middle-income (LMIC)

4. Line 69: How common are shared latrines? Can you cite a specific number? (See Berendes et al. 2017 10.1021/acs.est.6b06019)

5. Line 70: Substitute “may” for “can”

6. Line 78: The rainy season where? Or are you referencing rainy seasons in general?

7. Line 84-85: You mentioned the number of users here, but don’t discuss this later in the manuscript. Do you have this data? This seems like an important gap missing from you manuscript

8. Line 86-87: You mention users working collectively here. Did you collect any data on how users work together to clean their systems?

9. Lines 95-103: This reads like a list of studies rather than a concise introduction

10. Line 107-109: repetitive

11. Line 113: Disease and infection are not the same.

12. Line 140-141: You define public latrines later, so at the point it is unclear whether public latrines and shared latrines are the same thing

13. Line 172-173. Here you talk about non-respondents, but later you say you had 0 non-responses (Line 276). Which is it?

14. Line 173-177: This level of detail can go in the supplemental

15. Line 180: I would suggest you work these definitions into the manuscript naturally and can include these full definitions in the supplemental

16. Line 203: People may be illegally occupying land, but the people themselves are not illegal. I would suggest revising this definition

17. Line 212: too much detail

18. Line 276: What do you mean you “employed” study participants? Did you pay them?

19. Line 277: As you had a different number of cases and control I find it very confusing that you report your results as number(percentage). At minimum you need to included the denominator to these values. Since the sample size is different, it is much easier to compare the percentages than the raw values.

20. Line 300: Why may have some households been visited more often than others by the health extension workers? I expected to see this in the discussion

21. Line 306: Why may some households have better water access than others? Did you include household wealth or income as a covariate? I would assume wealthier households had better water access

22. Line 316: Can you provide a citation for why choose to compare income above and below the mean? I would have expected this to be quartiles or quintiles.

23. Line 319: You say “less likely” but the AOR is greater than 1. This data should be reported saying something like “Households who reported feeling privacy in their latrine had X times the odds of reporting to clean their latrine in the previous week compared to …”

24. Line 348: But was privacy associated with household income? Perhaps only high-income households could afford to build a private latrine.

25. Line 371: I find this interesting. Who are the health extension workers? How often do they typically visit? Why did they only visit some households?

26. Line 380: What was the water availability? Did all participants get their water from the same source? Additional context is needed in the results to contextualize this finding

Reviewer #2: This study uses an unmatched case-control design to assess barriers to cleaning of community latrines in Addis Ababa. Cases were those who did not clean latrines, and controls were those who did clean latrines based on self-report. Overall more information is required around how/why certain variables were selected for use in the logistic regression models (why demographic variables such as gender were not included) as well as details around recruitment methods. Finally, there is some confusion around the differences between data that were collected by observation compared to data collected in surveys, throughout the manuscript. Ideally these data should be reported an analyzed separately to reduce this confusion. My specific comments on each section of the manuscript are included below:

Background

In general, I find the Background section to be a bit too lengthy and I think that some content can be removed or shortened.

The final paragraph should include a succinct description of the study’s purpose (lines 126-127) which includes the study design and data used.

Line 70-71: “Shared facilities can reduce stress when proper maintenance and management systems are in place.” Please define what is meant by “stress” in this context.

Line 96-96: “Strina et al. found that people in latrine-owning 97 households in Salvador, Brazil behaved more hygienically than those without latrine.” Is this study looking at household latrines or shared latrines? This difference is very important to the underlying purpose of the manuscript, please be explicit.

Line 105-107: “Improving cleaning practices of shared latrines is a step toward achieving the United Nations’ 2030 goals for Sustainable Development, in line with achieving Target 6.2 of the Sustainable Development Goal (SDG) of universal access to sanitation as a key priority [29].” I think it may be useful to write out the exact wording of the Target and discuss how it does or does not apply to shared latrines.

Methods

Include a description around how study participants were recruited from the source population. How was the study introduced during the house-to-house visits, was there an IRB process?

How many individuals were considered non-respondents (line 173)?

Please describe what is meant by “regular monitoring by health extension workers”? Who is in charge of this monitoring and who determines which latrines are monitored?

In the paragraph beginning on line 225, please further explain how “validity” was assessed. Was it based on qualitative measurements? Provide more detail here.

In the description of the statistical analysis, explain how covariates were selected for the multivariable analysis. Why were certain questions included on the survey and in the model? Were there any survey questions that were not included in the final adjusted models?

The authors note that they assess multi-collinearity using standard errors, although this is not the correct method. The authors should calculate the variance inflation factor (VIF) and report those values.

Results

Line 316: explain why the cut-off income was $55.60, how was that value chosen?

Table 1: why is “divorced” the reference group in the logistic regression? The reference group is typically one of the more common groups, e.g., married or single. Same comment applies for the referent group select from the educational status and occupation variables.

Why is the “household size” variable entered as a binary variable rather than a continuous number of individuals per household measure?

Because you note that individuals in both the case and control group may be using the same latrines, I think what the survey is measuring is latrine perceptions rather than actual latrines data. For example, there were significant differences between cases and controls in reporting on privacy and whether the latrine had a door. If they are using the same latrines than this difference is based on their perceptions rather than actuality as there would be no difference there.

Do men and women use the same latrines? If not, analyses should be stratified by male/female respondent as they would be assessing a different set of latrines.

It is unclear throughout which data were collected in the surveys with participants and which data were collected using the observational checklist. This leads to a lot of confusion around whether you are talking about the latrine itself or individuals’ perceptions. These sets of data should have different samples sizes and should be reported and analyzed separately.

Discussion

Line 388 “This study used an unmatched case-control design and controlling of the confounders at the design stage was not possible.” Why was this not possible in this context? Also, why were no confounders (gender, age, etc) assessed during the analytic stage?

Finally, the manuscript included several grammatic mistakes throughout which should be addressed. For example:

- In Abstract: “barriers to keeping shared latrines cleaning”

- Line 138-139: “80% of Addis Ababa was slums”

- Line 371: “not regularly monitoring of the latrine”

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

29 Dec 2021

Line by line response to Reviewers for PONE-D-20-23172

Corresponding authors: Metadel Adane et al.

Dear Professor Hans-Uwe Dahms,

Thank you for your letter dated October 12, 2020 with a decision of revision needed. We were pleased to know that our manuscript was considered potentially acceptable for publication in PLoS ONE, subject to adequate revision as requested by the reviewers. Based on the instructions provided in your letter, we uploaded the file of the rebuttal letter; the marked-up copy of the revised manuscript highlighting the changes made in the original submitted version and the clean copy of the revised manuscript.

We addressed 67 questions/comments raised by the journal office staff, editor and two reviews. We are thankful for having so many questions. We have revised the manuscript by modifying the abstract, introduction, methods, results, discussion and other sections, based on the comments made by the reviewers and using the journal guidelines. Accordingly, we have marked in red color all the changes made during the revision process. Appended to this letter is our point-by-point response (rebuttal letter) to the comments made by the reviewers.

We agree with almost all the comments/questions raised by the reviewers and provided justification for disagreeing with some of them. We would like to take this opportunity to express our thanks to the reviewers for their valuable comments and to thank you for allowing us to resubmit a revision of the manuscript.

I hope that the revised manuscript is accepted for publication in PLoS ONE.

I am so sorry for being late in responding due to the COVID-19 crises.

Sincerely yours,

Metadel Adane (PhD)

Response to Journal office requirements

Q1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Answer: Thank you for this key comment: We formatted the manuscript with the PLoS ONE style. Please see the updated version.

Q2. Please clarify the relationship between the authors and the IRB. We typically expect at least one author to be affiliated with the institution which provides ethical oversight.

Answer: Thank you. The Ethical Considerations section has been updated to clarify this point. One of the significant contributors to the paper, Zewdie Aderaw Alemu, is affiliated with the GAMBY Medical and Business College, whose Institutional Review Board provided ethical clearance for the study. This contributor has been named as a co-author. Please see the revised ethical statement letter and the co-author affiliation.

Q3. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Response: We have received the support of a professional language editor whose name is Lisa Penttila from Canada. We hope that the language usage, spelling, and grammar is now acceptable. Please see the updated manuscript.

Q4. Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses.

Response: Thank you for this important comment. We provided detailed information regarding the survey/questionnaire used in the study in the Method section of the page 9 from lines 194 and 195. This will help to ensure that others could replicate the analyses. We also included the questionnaire as supporting information SI and SII. Please see page 19.

Q5. Please amend either the title on the online submission form (via Edit Submission) or the title in the manuscript so that they are identical.

Response: We have made the amendment to ensure the title is consistent between the manuscript and online submission system. Thank you.

Q6. We note that Figure 1 in your submission contains map images which may be copyrighted.

Response: Thank you for your concern. Figure 1 has been deleted since the text contains the key geographic information.

Response the academic editor

Additional Editor Comments:

Q1. Pls. consider and REVISE your MS particularly following REVIEWER 1 who otherwise rejected your contribution!

Response: Thank you. We carefully addressed reviewer 1 and other reviewer comments.

Q2. This study uses an unmatched case-control design to assess barriers to cleaning of community latrines in Addis Ababa. Cases were those who did not clean latrines, and controls were those who did clean latrines based on self-report. Overall more information is required around how/why certain variables were selected for use in the logistic regression models (why demographic variables such as gender were not included) as well as details around recruitment methods. Finally, there is some confusion around the differences between data that were collected by observation compared to data collected in surveys, throughout the manuscript. Ideally these data should be reported an analyzed separately to reduce this confusion. My specific comments on each section of the manuscript are included below:

Response: Dear Prof Hans, thank you for your comment. Gender was excluded from the multivariable analysis due to the fact that the p-value from the bivariate analysis was greater than 2.5. Variables were selected to the multivariable analysis only if the p-value from the bivariate analysis was less than 0.25.

We also briefly pointed out that data was measured by observation and interviewing in the Method section on page 11 from lines 249 to 256-. However, after proper categorization of variables, both types of variables (those measured by observation and by interview) were considered in the same data reporting and analyzed in the same model of unconditional logistic regression, which is also the most common way of data management during logistic regression. Please see below for several similar studies that I handled in this way.

Similar papers link about

• https://doi.org/10.1371/journal.pone.0182783

• https://doi.org/10.1371/journal.pone.0181516

• DOI: 10.1007/s10900-017-0437-1

Background

Q3. In general, I find the Background section to be a bit too lengthy and I think that some content can be removed or shortened.

Response: Thank you for this key feedback. We revised the background section as suggested. Please see the Background of the revised version. We reduced the length by about a third.

Q4. The final paragraph should include a succinct description of the study’s purpose (lines 126-127) which includes the study design and data used.

Response: We included the purpose of the study, study design and data used. Please see the last paragraph of the Background section.

Q5. Line 70-71: “Shared facilities can reduce stress when proper maintenance and management systems are in place.” Please define what is meant by “stress” in this context.

Response: To clarify this sentence, we replaced the term “stress” with another positive term. See page --- lines -----

Q6. Line 96-96: “Strina et al. found that people in latrine-owning 97 households in Salvador, Brazil behaved more hygienically than those without latrine.” Is this study looking at household latrines or shared latrines? This difference is very important to the underlying purpose of the manuscript, please be explicit.

Response: Thank you for this key comment. Since the study of Strina et al. was about household latrines and our study is about shared latrines, we deleted the idea of Strina et al.

Q7. Line 105-107: “Improving cleaning practices of shared latrines is a step toward achieving the United Nations’ 2030 goals for Sustainable Development, in line with achieving Target 6.2 of the Sustainable Development Goal (SDG) of universal access to sanitation as a key priority [29].” I think it may be useful to write out the exact wording of the Target and discuss how it does or does not apply to shared latrines.

Response: Thank you for this valuable comment. In order to make the Background section shorter as suggested above, ideas about SDGs were deleted.

Methods

Q8. Include a description around how study participants were recruited from the source population. How was the study introduced during the house-to-house visits, was there an IRB process?

Response: Thank you for this important comment. We provided detailed information about the study participant recruitment, house-to-house visits and about ethical consideration. Please see the Method section on page 9 about study participant recruitment, page 10 about home visits and page 11 about IRB process.

Q9. How many individuals were considered non-respondents (line 173)?

Response: Unfortunately in this study, there were no non-respondents, which might be due to the random selection of cases and controls based on the self-report of latrine cleaning condition (cleaned or not cleaned) until the sample size was achieved. We provided detailed information about this in the description of the sampling procedure on page 9.

Q10. Please describe what is meant by “regular monitoring by health extension workers”? Who is in charge of this monitoring and who determines which latrines are monitored?

Response: Regular monitoring of latrines by health extension workers is a part of Ethiopia’s community-based Health Extension Program. Each district health bureau assigns a health extension worker to monitor the execution of Health Extension Package programs such as solid waste management, latrine cleaning, water handling practice and so on. The district health bureau tracks the weekly and monthly reports of each health extension worker, while each district health bureau is in turn monitored by the sub-city health office.

Q11. In the paragraph beginning on line 225, please further explain how “validity” was assessed. Was it based on qualitative measurements? Provide more detail here.

Response: Thank you for bringing attention to this key issue. To ensure the quality of the data, we also pre-tested the questionnaire among 10 cases and 20 control households (10% of the sample size) in one non-selected area of District 4 in Lideta Sub-City to evaluate its face and content validity. During the pre-test, face validity was checked to verify that the questions measured what they were intended to measure. Content validity was also checked by three experts re (environmental health professionals) who ensured that the survey contained questions that covered all aspects of the construct being measured. Data collection began after we approved the face and content validity of the survey tool.

Q12. In the description of the statistical analysis, explain how covariates were selected for the multivariable analysis. Why were certain questions included on the survey and in the model? Were there any survey questions that were not included in the final adjusted models?

Response: For variable selection to the final model, variables (covariates) with a p-value less than 0.25 from bivariate analysis were included to the multivariable analysis. Some variables such as sex and age were not included in the final model due to the fact that the p-value from the bivariate analysis were greater than or equal to 0.25. Please see the detailed information about data analysis on page 11.

Q13. The authors note that they assess multi-collinearity using standard errors, although this is not the correct method. The authors should calculate the variance inflation factor (VIF) and report those values.

Response: The presence of multi-collinearity among independent variables was also checked using variance inflation factor (VIF) and we found a maximum VIF of 2.0, which indicated there was no multi-collinearity between independent variables.

Results

Q14. Line 316: explain why the cut-off income was $55.60, how was that value chosen?

Response: The cut-off income $55.6 was determined based on the mean value of the income.

Table 1: why is “divorced” the reference group in the logistic regression? The reference group is typically one of the more common groups, e.g., married or single. Same comment applies for the referent group select from the educational status and occupation variables.

Response: We selected the reference category depending on the direction of the association found during the analysis. When we selected the most frequent common group, it was found to be a preventive factor, which was odds ratio and confidence interval below 1. However, since we were studying associated factors, direction of association should be towards positive rather than explaining the findings of the preventive factors that has a negative direction of association.

Q15. Why is the “household size” variable entered as a binary variable rather than a continuous number of individuals per household measure?

Response: During the binary logistic regression model analysis, continuous variables must be changed to categorical variables. Continuous variables such as household size were entered to the model if the model of data analysis used linear regression. But since our model used binary logistic regression, variables entered to the model had to have a certain category with reference group. Following this rule for logistic regression, continuous variables were changed to categorical variables.

Q16. Because you note that individuals in both the case and control group may be using the same latrines, I think what the survey is measuring is latrine perceptions rather than actual latrines data. For example, there were significant differences between cases and controls in reporting on privacy and whether the latrine had a door. If they are using the same latrines than this difference is based on their perceptions rather than actuality as there would be no difference there.

Response: Thank you for this concern. In this study, that cases and control should not use the same latrine was one of the criteria used during selection of case and control. Wording has been revised to make this point clear.

Q17. Do men and women use the same latrines? If not, analyses should be stratified by male/female respondent as they would be assessing a different set of latrines.

Response: Yes, men and women used the same latrine if they lived in the same household or if their households shared the same latrine. In slums of Addis Ababa, shared latrines are not classified for men or women, although this division exists in hotels, cafes and restaurants.

Q18. It is unclear throughout which data were collected in the surveys with participants and which data were collected using the observational checklist. This leads to a lot of confusion around whether you are talking about the latrine itself or individuals’ perceptions. These sets of data should have different samples sizes and should be reported and analyzed separately.

Response: We provided detail information about variables collected by observation and interviewing. Please see page 9. Thank you for this valuable concern.

Discussion

Q19. Line 388 “This study used an unmatched case-control design and controlling of the confounders at the design stage was not possible.” Why was this not possible in this context? Also, why were no confounders (gender, age, etc) assessed during the analytic stage?

Response: Although controlling of the confounders at the design stage would be performed for a matched case-control study, our study used an unmatched case-control design, so confounders were controlled during data analysis, but not at the design stage. This is a principle of the difference between matched and unmatched case-control designs. However, in our study, confounders such as gender and age were assessed during the analysis stage. Thus, one of the limitations of this study was its unmatched case-control study design, which did not help to control confounders at the design stage; whereas using matched case-control design may provide better evidence due to the fact that potential confounders can be controlled at the design stage during matching of cases and controls using certain expected confounder variables.

Q20. Finally, the manuscript included several grammatic mistakes throughout which should be addressed. For example:

- In Abstract: “barriers to keeping shared latrines cleaning”

- Line 138-139: “80% of Addis Ababa was slums”

- Line 371: “not regularly monitoring of the latrine”

Response: We regret these errors and have made revisions as noted.

�  The word ”keeping” was deleted in the Abstract.

�  “80% of Addis Ababa was slums” was changed to “four-fifths (80%) of Addis Ababa was classified as slums”.

�  The noted phrase “not regularly monitoring of the latrine” was changed to “not regularly monitoring the latrine”.

Line by line response to reviewers

Reviewer #1:

Q1. The authors investigated the barriers to cleaning shared latrines in Addis Ababa, Ethiopia. The authors conducted a rigorous household survey and attempt to explain their findings in the manuscript. I commend the authors for the substantial improvements to the manuscript. In particular, the manuscript is substantially improved in its engagement with the broader literature and the writing is improved. As with the previous manuscript, the study appears well designed and the data sound, but I still find the manuscript unsuitable for publication in its current form. Another round of substantial revisions are needed. The manuscript is very repetitive, there are too many details in the abstract, the writing unclear at certain points, there are numerous grammatical mistakes, the statistical analysis is incomplete and unclear, there is little discussion on the limitations, and the some of the recommendations are generic. Further, I would suggest you make use of the supplemental information to make the manuscript more concise.

Response: We really appreciate your scientific input. We updated the Abstract, minimized the repetition in the Background section, corrected grammatical errors and also we made revisions to the Limitations section. Please see all sections in the revised manuscript. We also strengthened the specificity of the conclusion based on the findings.

Main Comments

Q2. There are too many details in the abstract. Line 30-37 is too much detail. Line 46-50 is a repetition of the previous sentence.

Response: We minimize details in lines 30-37 and we also deleted line 46-50 to avoid repetition. Thank you.

Q3. Line 35. Here and throughout you never mention what covariates you used in your adjusted analysis

Response: Sorry for the confusion. In the data analysis, we briefly mentioned the selection of covariates for the adjusted analysis. Please see the Method section on page 11.

Q4. Line 50-54: These recommendations are too generic. This manuscript offers an opportunity to make credible suggestions to an interested audience. Increasing household income is a noble aim but is not a feasible recommendation from this data.

Response: We revised the recommendations. We deleted increasing household income as a recommendation in the abstract. Please see the revised version of the abstract.

Q5. The introduction is insufficiently focused and should not be a mini-review of the broader field.

Response: We accept your comment. We revised the introduction to make it more focused. Please see the whole Introduction section. Thank you.

Q6. Line 145: How were study participants selected? Was it every member of District 05 (line 152)? This is unclear to me.

Response: Thank you for this key comment. We provided detailed information about how the study participants selected. By house-to-house visits, cases were randomly selected from those who reported they had not cleaned the shared latrine at least once during the week prior to data collection and controls were selected from shared latrine users who reported they had cleaned the latrine at least once during the week prior to data collection.

Study participants who were not available during the survey were revisited once on the same day or the next day. If not available again, a third visit was made and if not available again, the study participant would be considered a non-respondent; however, in this study there was no non-respondents, which might be due to the random selection of cases and controls based on the self-report of latrine cleaning condition (cleaned or not cleaned) before the sample size was achieved. See the sampling procedure on page 7 and 8.

Q7. Again on Line 168. Did you visit every household?

Response: Only households that used shared latrines were visited. Households that used private latrines were not part of the study and not visited. Households were visited during identification of cases and controls.

Q8. Lines 218-223: Is this the only data that you collected? Or are you only reporting the statistically significant data? It seems like you ran a lot of models, and to avoid accusations of p-hacking, you should adjust your analysis for multiple comparisons.

Response: We listed variables for collected data in the Method section. However, during discussion, we only discussed for those significant variables. We ran only one model and adjusted analysis performed to control confounders. Please see the data analysis section on page 11.

Q9. Line 253. This citation is not sufficient here. You need to explain what covariates you used in your adjusted models.

Response: We fixed a cut-off point to include covariates for the adjusted model. Listing those variables in the data analysis would add unnecessary repetition of ideas, we believe. However, for variable selection to the final model, variables with a p-value less than 0.25 from bivariate analysis were included to the multivariable analysis.

Q10. Line 316: You calculated odds ratios, not risk ratios. Please make sure the language you use accurately explains your results. As written, this is incorrect.

Response: Thank you. We deleted the term “risk” throughout the paper.

Q11. You calculated odds ratios, which are a measure of association, not causation. The discussion section needs to reflect this.

Response: Thank you. We updated the discussion accordingly.

Q12. Line 334: All the associations you observed could be explain by poverty. If you did not adequately adjust for household wealth or income in your analysis, these finding may be spurious.

Response: We adjusted for income in the final model and found it is one of the factors for not cleaning the shared larine. We believe that our analysis is correct. We appreciate your comment.

Q13. Line 388: Further discussion of the limitations of this study are needed. What potential sources of bias may have influenced your results?

Response: We improved the Limitations section as suggested. The self-reported data such as household income, may have bias by underestimate or overestimate. Furthermore, the sanitation and hygiene status of the latrine may be reported wrongly, although most of the data was collected using on-the-spot observational checklist. During observation, there may also have been bias of the data collector. For instance, latrines that were clean during data collection may have been classified as unclean. Please see the limitation on page 18.

Q14. The language in the conclusion needs to better reflect that you found associations, not causation

Response: Thank you. We improved the conclusion with this in mind.

Q15. This manuscript may be more suited for a more specialized journal, such as the Journal of Water, Sanitation, and Hygiene for Development

Response: Yes, this is reasonable comment. But we found that PLoS ONE has a high impact factor, whereas Journal of Water, Sanitation, and Hygiene for Development has a lower impact factor. We are interested in publishing in a high impact factor journal.

Minor Comments:

Q16. Line 25: As currently written, you are implying there currently is a comprehensive sanitation program in this setting? Is that true?

Response: No. We updated the sentence. Please see Abstract again.

Q17. Line 42-46. Why do you use 1 significant figure for some values and 2 significant figures for others?

Response: Sorry for the confusion. We used two significant figures (two digits). Thank you. See the Abstract Result section.

Q18. Line 65: All countries are developing. I would suggest you refer to these countries as low- and middle-income (LMIC)

Response: Thank you for this key comment. We updated as suggested. Please see the first line of the introduction.

Q19. Line 69: How common are shared latrines? Can you cite a specific number? (See Berendes et al. 2017 10.1021/acs.est.6b06019)

Response: The term common has been deleted to avoid confusion.

Q20. Line 70: Substitute “may” for “can”

Response: Done

Q21. Line 78: The rainy season where? Or are you referencing rainy seasons in general?

Response: Yes, we are referencing rainy seasons in general. Thank you.

Q22. Line 84-85: You mentioned the number of users here, but don’t discuss this later in the manuscript. Do you have this data? This seems like an important gap missing from you manuscript

Response: Thank you, we deleted it.

Q23. Line 86-87: You mention users working collectively here. Did you collect any data on how users work together to clean their systems?

Response: To avoid confusion, the term “collectively” is changed to “together”. 9. Lines 95-103: Q24. This reads like a list of studies rather than a concise introduction

Response: Very nice feedback. We deleted this material. Please see the revised version.

Q25. 10. Line 107-109: repetitive

Response: We agreed and deleted it.

Q26. Line 113: Disease and infection are not the same.

Response: Yes, we deleted the term “infection” and made the information about “disease”.

Q27. Line 140-141: You define public latrines later, so at the point it is unclear whether public latrines and shared latrines are the same thing

Response: Thank you. We revised the sentence. This study was conducted among shared latrine users. A public latrine is one type of shared latrine. Shared latrine means that a latrine is shared by two or more households.

Q28. Line 172-173. Here you talk about non-respondents, but later you say you had 0 non-responses (Line 276). Which is it?

Response: Study participants who were not available during the survey were revisited once on the same day or the next day. If not available again, a third visit was made, and if not available again, the study participant was considered a non-respondent; however, in this study there was no non-respondent, which might be due to the random selection of cases and controls based on the self-report of latrine cleaning condition (cleaned or not cleaned) until the sample size achieved.

Q29. Line 173-177: This level of detail can go in the supplemental

Response: We condensed the ideas of Line 173 to 177. Thank you.

Q30. Line 180: I would suggest you work these definitions into the manuscript naturally and can include these full definitions in the supplemental

Response: Including the definitions in the supplemental may create confusion for readers once published. We feel that since the operational definitions are key for measurement, it is useful to include them in the Method section of the manuscript.

Q31. Line 203: People may be illegally occupying land, but the people themselves are not illegal. I would suggest revising this definition

Response: We re-defined as “slums are areas dominated by informal settlements that are characterized by one or more of the five characteristics of overcrowding, poor sanitation, insecure land tenure, lack of access to water supply, poor housing quality and other infrastructure.

Q32. Line 212: too much detail

Response: We tried to minimize it. Please see the revised version on page

Q33. Line 276: What do you mean you “employed” study participants? Did you pay them?

Response: The term employed was deleted to avoid confusion. We mean that the study included 300 study participants.

Q34. Line 277: As you had a different number of cases and control I find it very confusing that you report your results as number (percentage). At minimum you need to include the denominator to these values. Since the sample size is different, it is much easier to compare the percentages than the raw values.

Response: Since the sample size for cases were 100 and the denominator was 100, when the percentage was calculated for any number out of 100%, it would be similar. For example 30 becomes 30% and 40 become 40%. However, the percentage and number for controls are different since the denominator was 200.

Q35. Line 300: Why may have some households been visited more often than others by the health extension workers? I expected to see this in the discussion

Response: We updated the Discussion section. Please see page 15 to 18.

Q36. Line 306: Why may some households have better water access than others? Did you include household wealth or income as a covariate? I would assume wealthier households had better water access

Response: Thank you for this valuable comment. Access to water might depend on household income variation, as you mentioned. We considered income as one of the covariates and adjusted for analysis. We also found that low income is one of the factors for not cleaning the latrine.

Q37. Line 316: Can you provide a citation for why choose to compare income above and below the mean? I would have expected this to be quartiles or quintiles.

Response: The study was conducted among the poor community in urban areas and considered only income and did not consider other assets. A wealth index that classifies in quartiles or quintiles should consider not only income but also other kind and in-kind assets. Therefore, we used only mean of the income to categorize variation.

Q38. Line 319: You say “less likely” but the AOR is greater than 1. This data should be reported saying something like “Households who reported feeling privacy in their latrine had X times the odds of reporting to clean their latrine in the previous week compared to …”

Response: This was a major problem. We did the revision accordingly. We thank you so much. Please see the updated version on page 14.

Q39. Line 348: But was privacy associated with household income? Perhaps only high-income households could afford to build a private latrine.

Response: Yes, privacy may be associated with household income, but in our case, we did not study the association between privacy and household income. However, in normal circumstances, they have a have direct relationship since high-income households could afford to build a private latrine.

Q40. Line 371: I find this interesting. Who are the health extension workers? How often do they typically visit? Why did they only visit some households?

Response: Health extension workers are health professionals assigned at kebele (administrative unit roughly equal to a neighborhood) level for improvement of the health system. This is a new innovation by the Ethiopia Ministry of Health where over 30,000 health extension workers are deployed throughout Ethiopia. The Health Extension Program is one the main health packages in Ethiopia. See the details about the Health Extension Program on page 17.

Q41. Line 380: What was the water availability? Did all participants get their water from the same source? Additional context is needed in the results to contextualize this finding

Response: “This study also indicates that lack of water availability is one of the barriers to cleaning shared latrines. In our study setting, the source of the water is the same government supply for all. However, due to the presence of water supply interruptions, the availability of water at home varied and depended on whether a household stored water or not. Some households may also purchase water to cope with problems encountered during an interruption. Please see the Discussion section on page 17.

Reviewer #2:

Q1. Pls. consider and REVISE your MS particularly following REVIEWER 1 who otherwise rejected your contribution!

Response: Thank you. We carefully addressed reviewer 1 and other reviewer comments.

Q2. This study uses an unmatched case-control design to assess barriers to cleaning of community latrines in Addis Ababa. Cases were those who did not clean latrines, and controls were those who did clean latrines based on self-report. Overall more information is required around how/why certain variables were selected for use in the logistic regression models (why demographic variables such as gender were not included) as well as details around recruitment methods. Finally, there is some confusion around the differences between data that were collected by observation compared to data collected in surveys, throughout the manuscript. Ideally these data should be reported an analyzed separately to reduce this confusion. My specific comments on each section of the manuscript are included below:

Response: Dear Prof Hans, thank you for your comment. Gender was excluded from the multivariable analysis due to the fact that the p-value from the bivariate analysis was greater than 2.5. Variables were selected to the multivariable analysis only if the p-value from the bivariate analysis was less than 0.25.

We also briefly pointed out that data was measured by observation and interviewing in the Method section on page 11 from lines 249 to 256-. However, after proper categorization of variables, both types of variables (those measured by observation and by interview) were considered in the same data reporting and analyzed in the same model of unconditional logistic regression, which is also the most common way of data management during logistic regression. Please see below for several similar studies that I handled in this way.

Similar papers link about

• https://doi.org/10.1371/journal.pone.0182783

• https://doi.org/10.1371/journal.pone.0181516

• DOI: 10.1007/s10900-017-0437-1

Background

Q3. In general, I find the Background section to be a bit too lengthy and I think that some content can be removed or shortened.

Response: Thank you for this key feedback. We revised the background section as suggested. Please see the Background of the revised version. We reduced the length by about a third.

Q4. The final paragraph should include a succinct description of the study’s purpose (lines 126-127) which includes the study design and data used.

Response: We included the purpose of the study, study design and data used. Please see the last paragraph of the Background section.

Q5. Line 70-71: “Shared facilities can reduce stress when proper maintenance and management systems are in place.” Please define what is meant by “stress” in this context.

Response: To clarify this sentence, we replaced the term “stress” with another positive term.

Q6. Line 96-96: “Strina et al. found that people in latrine-owning 97 households in Salvador, Brazil behaved more hygienically than those without latrine.” Is this study looking at household latrines or shared latrines? This difference is very important to the underlying purpose of the manuscript, please be explicit.

Response: Thank you for this key comment. Since the study of Strina et al. was about household latrines and our study is about shared latrines, we deleted the idea of Strina et al.

Q7. Line 105-107: “Improving cleaning practices of shared latrines is a step toward achieving the United Nations’ 2030 goals for Sustainable Development, in line with achieving Target 6.2 of the Sustainable Development Goal (SDG) of universal access to sanitation as a key priority [29].” I think it may be useful to write out the exact wording of the Target and discuss how it does or does not apply to shared latrines.

Response: Thank you for this valuable comment. In order to make the Background section shorter as suggested above, ideas about SDGs were deleted.

Methods

Q8. Include a description around how study participants were recruited from the source population. How was the study introduced during the house-to-house visits, was there an IRB process?

Response: Thank you for this important comment. We provided detailed information about the study participant recruitment, house-to-house visits and about ethical consideration. Please see the Method section on page 9 about study participant recruitment, page 10 about home visits and page 11 about IRB process.

Q9. How many individuals were considered non-respondents (line 173)?

Response: Unfortunately in this study, there were no non-respondents, which might be due to the random selection of cases and controls based on the self-report of latrine cleaning condition (cleaned or not cleaned) until the sample size was achieved. We provided detailed information about this in the description of the sampling procedure on page 9.

Q10. Please describe what is meant by “regular monitoring by health extension workers”? Who is in charge of this monitoring and who determines which latrines are monitored?

Response: Regular monitoring of latrines by health extension workers is a part of Ethiopia’s community-based Health Extension Program. Each district health bureau assigns a health extension worker to monitor the execution of Health Extension Package programs such as solid waste management, latrine cleaning, water handling practice and so on. The district health bureau tracks the weekly and monthly reports of each health extension worker, while each district health bureau is in turn monitored by the sub-city health office.

Q11. In the paragraph beginning on line 225, please further explain how “validity” was assessed. Was it based on qualitative measurements? Provide more detail here.

Response: Thank you for bringing attention to this key issue. To ensure the quality of the data, we also pre-tested the questionnaire among 10 cases and 20 control households (10% of the sample size) in one non-selected area of District 4 in Lideta Sub-City to evaluate its face and content validity. During the pre-test, face validity was checked to verify that the questions measured what they were intended to measure. Content validity was also checked by three experts re (environmental health professionals) who ensured that the survey contained questions that covered all aspects of the construct being measured. Data collection began after we approved the face and content validity of the survey tool.

Q12. In the description of the statistical analysis, explain how covariates were selected for the multivariable analysis. Why were certain questions included on the survey and in the model? Were there any survey questions that were not included in the final adjusted models?

Response: For variable selection to the final model, variables (covariates) with a p-value less than 0.25 from bivariate analysis were included to the multivariable analysis. Some variables such as sex and age were not included in the final model due to the fact that the p-value from the bivariate analysis were greater than or equal to 0.25. Please see the detailed information about data analysis on page 11.

Q13. The authors note that they assess multi-collinearity using standard errors, although this is not the correct method. The authors should calculate the variance inflation factor (VIF) and report those values.

Response: The presence of multi-collinearity among independent variables was also checked using variance inflation factor (VIF) and we found a maximum VIF of 2.0, which indicated there was no multi-collinearity between independent variables.

Results

Q14. Line 316: explain why the cut-off income was $55.60, how was that value chosen?

Response: The cut-off income $55.6 was determined based on the mean value of the income.

Table 1: why is “divorced” the reference group in the logistic regression? The reference group is typically one of the more common groups, e.g., married or single. Same comment applies for the referent group select from the educational status and occupation variables.

Response: We selected the reference category depending on the direction of the association found during the analysis. When we selected the most frequent common group, it was found to be a preventive factor, which was odds ratio and confidence interval below 1. However, since we were studying associated factors, direction of association should be towards positive rather than explaining the findings of the preventive factors that has a negative direction of association.

Q15. Why is the “household size” variable entered as a binary variable rather than a continuous number of individuals per household measure?

Response: During the binary logistic regression model analysis, continuous variables must be changed to categorical variables. Continuous variables such as household size were entered to the model if the model of data analysis used linear regression. But since our model used binary logistic regression, variables entered to the model had to have a certain category with reference group. Following this rule for logistic regression, continuous variables were changed to categorical variables.

Q16. Because you note that individuals in both the case and control group may be using the same latrines, I think what the survey is measuring is latrine perceptions rather than actual latrines data. For example, there were significant differences between cases and controls in reporting on privacy and whether the latrine had a door. If they are using the same latrines than this difference is based on their perceptions rather than actuality as there would be no difference there.

Response: Thank you for this concern. In this study, that cases and control should not use the same latrine was one of the criteria used during selection of case and control. Wording has been revised to make this point clear.

Q17. Do men and women use the same latrines? If not, analyses should be stratified by male/female respondent as they would be assessing a different set of latrines.

Response: Yes, men and women used the same latrine if they lived in the same household or if their households shared the same latrine. In slums of Addis Ababa, shared latrines are not classified for men or women, although this division exists in hotels, cafes and restaurants.

Q18. It is unclear throughout which data were collected in the surveys with participants and which data were collected using the observational checklist. This leads to a lot of confusion around whether you are talking about the latrine itself or individuals’ perceptions. These sets of data should have different samples sizes and should be reported and analyzed separately.

Response: We provided detail information about variables collected by observation and interviewing. Please see page 9. Thank you for this valuable concern.

Discussion

Q19. Line 388 “This study used an unmatched case-control design and controlling of the confounders at the design stage was not possible.” Why was this not possible in this context? Also, why were no confounders (gender, age, etc) assessed during the analytic stage?

Response: Although controlling of the confounders at the design stage would be performed for a matched case-control study, our study used an unmatched case-control design, so confounders were controlled during data analysis, but not at the design stage. This is a principle of the difference between matched and unmatched case-control designs. However, in our study, confounders such as gender and age were assessed during the analysis stage. Thus, one of the limitations of this study was its unmatched case-control study design, which did not help to control confounders at the design stage; whereas using matched case-control design may provide better evidence due to the fact that potential confounders can be controlled at the design stage during matching of cases and controls using certain expected confounder variables.

Q20. Finally, the manuscript included several grammatic mistakes throughout which should be addressed. For example:

- In Abstract: “barriers to keeping shared latrines cleaning”

- Line 138-139: “80% of Addis Ababa was slums”

- Line 371: “not regularly monitoring of the latrine”

Response: We regret these errors and have made revisions as noted.

�  The word ”keeping” was deleted in the Abstract.

�  “80% of Addis Ababa was slums” was changed to “four-fifths (80%) of Addis Ababa was classified as slums”.

�  The noted phrase “not regularly monitoring of the latrine” was changed to “not regularly monitoring the latrine”.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

19 Jan 2022

Barriers to Cleaning of Shared Latrines in Slums of Addis Ababa, Ethiopia

PONE-D-20-23172R1

Dear Dr. Adane,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Hans-Uwe Dahms, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

On the 12th October 12, 2020 I decided on major revision of this contribution.

The authors then addressed 67 questions/comments raised by the journal office staff, myself and two reviews.

The MS was now revised by modifying the abstract, introduction, methods, results, discussion and other sections,

based on the comments made by the reviewers and using the journal guidelines. The authors agreed with most of the

comments/questions raised by the reviewers and provided justification for disagreeing with some of them. The additional

author Zewdie Aderaw Alemu is accepted considering his contribution during the research work and during the revision

of the manuscript.END

Reviewers' comments:

28 Feb 2022

PONE-D-20-23172R1

Barriers to cleaning of shared latrines in slums of Addis Ababa, Ethiopia

Dear Dr. Adane:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Hans-Uwe Dahms

Academic Editor

PLOS ONE