Literature DB >> 32842993

Prevalence and associations of active trachoma among rural preschool children in Wadla district, northern Ethiopia.

Mesfin Wudu Kassaw1, Ayele Mamo Abebe2, Kirubel Dagnaw Tegegne3, Mikiyas Amare Getu4, Woldemichael Tadesse Bihonegn5.   

Abstract

BACKGROUND: Trachoma is a neglected eye disease and an important cause of preventable corneal blindness. In endemic areas, initial infection can occur in early childhood and following a recurrent episodes, it progresses to scarring and visual impairment. Trachoma disappeared from high income countries through enhancements of hygiene and sanitation but the disease is still a challenge in developing countries. In Ethiopia, data indicate that Amhara is the region with the highest prevalence of active trachoma. The aim of this study was to assess the prevalence and associations of active trachoma among rural preschool children in Wadla district, Amhara region, Ethiopia.
METHODS: In this study, 596 children were screened for signs of active trachoma by using cluster-sampling technique. Following pre-testing of the survey instrument in a different district, questions about socio-demographic status were delivered for heads of households. Integrated eye care workers, previously trained to undertake trachoma screening for one month, performed eye examination. The logistic regression model was used to look for associations of active trachoma.
RESULTS: The prevalence of active trachoma among rural preschool children in Wadla district was 22%. Low economic status (adjusted odds ratio [AOR]3.8 (95%CI 1.3-11.4), being 37-48 months old (4.2;1.5-12.0), living in a house with thatched roof (4.4;1.4-13.6), presence of flies in a home (4.6;2.1-9.9), once-weekly face-washing frequency (8.6;2.5-29.3), having a face that had not been washed for longer than a week (10.6;2.9-37.7), and not using soap (4.5;1.8-11.3) had association to active trachoma.
CONCLUSION: The prevalence of active trachoma among rural pre-school children in Wadla district was high. This indicates that Trachoma is still a public health problem in the district. This high prevalence calls for further interventions to prevent future trachomatis blindness.

Entities:  

Keywords:  Active trachoma; Associations; Ethiopia; Hygiene; Sanitation; Wadla district; Water

Mesh:

Year:  2020        PMID: 32842993      PMCID: PMC7449018          DOI: 10.1186/s12886-020-01585-9

Source DB:  PubMed          Journal:  BMC Ophthalmol        ISSN: 1471-2415            Impact factor:   2.209


Background

Trachoma is a neglected eye disease and an important cause of preventable corneal blindness [1, 2], which is categorized into active and cicatricial types of trachoma [2, 3]. In endemic areas, cycles of infection with Chlamydia trachomatis progress to scarring, trachomatis trichiasis, and corneal opacity [4-6]. Trachoma is a disease of poverty and poor hygiene [7] that found primarily in children [4], with the late-stage disease more frequently seen in adult women than adult men, possibly because of women’s greater time spent in proximity to children. Pieces of literature indicate that preschool children are the main pool of ocular C. trachomatis infection [8, 9].Active trachoma can be an extremely common problem in children, with prevalence estimates of 60–90% [10]. Ocular C. trachomatis is believed to be transmitted through hand-to-hand contact, sharing of towels, fomites, pillows, and eye-seeking flies [11]. Globally, an estimated 2.5 million people had trachomatis trichiasis, needing surgery (S) to prevent ongoing visual impairment. Another nearly 142 million people lived in districts in which the prevalence of active trachoma met WHO-defined criteria for intervention with antibiotics (A) and interventions to promote facial cleanliness (F) and improve the environment (E), in order to prevent future trichiasis cases. Ethiopia is the most trachoma affected country: more than half of the 142 million people needing the A, F and E components of the “SAFE strategy” in 2019 lived here, Ethiopia [12]. Within Ethiopia, Amhara region has the highest trachoma burden [13], although, the prevalence and associations of active trachoma vary from setting to setting. Hence, studying the differences may help to tailor local control approaches. This is why we undertook investigations in Wadla district, Amhara region after 5 successive years of Zithromax administration in order to re-estimate the prevalence of active trachoma and examine its associations.

Methods

Study design, period and setting

A community-based cross-sectional study design was used. Fieldwork was undertaken from March 11, 2017 to April 26, 2107. The estimated population of Wadla district was 128,170 with 64,574 males and 63,596 females. There were 28,414 households in this district with an average of 4.5 persons per house. The district had 1 general hospital, 7 health centers, and 20 health posts.

Population

The sampling frame was children aged 1 to 5 years old in 150 rural villages of Wadla district. The study units were heads from the selected rural households that also had preschool children.

Sample size determination

We estimated the required sample size using the single population proportion formula. We assumed, based on previous surveys, an observed prevalence of active trachoma (12.1%) [14], which we wished to estimate with 95% confidence within ±5%. We used a design effect of 1.5, and allowed for 10% non- response rate. Through multiplying the sample size by the design effect, 1.5 and incorporating a 10% non-response rate, we estimated273 children that were needed to be framed in selected households.

Sampling technique

A multistage cluster sampling technique was applied. Wadla district had 20 kebeles (sub-districts) that comprise 247 villages. Twelve of the kebeles were rural, whereas eight of the kebeles were urban. Regarding the villages, 150 of the 247 villages were rural. We used simple random sampling to select 30 of the 150 rural villages. There were 967 households in the selected 30 villages, but only 499 of those households had preschool children. Thus, those 499 households were visited. Heads of households were interviewed for socio-demographic and economic information, plus housing and environmental conditions, and all children aged between 1 and 5 years who had been resident in the district for at least six months were invited to be examined. Eye examiners used the WHO simplified trachoma grading scheme to grade signs of trachoma [15] (Fig. 1).
Fig. 1

: The schematic diagram of sampling procedure in selecting preschool children from rural Wadla district, northern Ethiopia, 2017. The sample size calculated was 273 using single population proportion formula, but as the sampling procedure was cluster sampling, the numbers of screened children were 596 from all 30 villages.

: The schematic diagram of sampling procedure in selecting preschool children from rural Wadla district, northern Ethiopia, 2017. The sample size calculated was 273 using single population proportion formula, but as the sampling procedure was cluster sampling, the numbers of screened children were 596 from all 30 villages.

Definitions

Clean face

A face of child that was free of eye discharges, nose discharges or flies at the time of eye examination.

Preschool

Children whose age were greater than and equal to 1 year and less than or equal to 5 years old.

Village

A grouping of homes that contained at least 30 households organized as one peasant association.

Fly in a home

When there is/are a countable fly in a house during data collection, despite the number of flies.

Active trachoma

The presence of at least one of the two signs of active trachoma according to the WHO simplified trachoma grading scheme (TF or TI) in at least one eye [16].

Trachomatis inflammation—follicular (TF)

The presence of five or more follicles each having a diameter of at least 0.5 mm in the central part of the upper tarsal conjunctiva [16].

Trachomatis inflammation—intense (TI)

A pronounced inflammatory thickening of the upper tarsal conjunctiva that obscures more than half of the normal deep tarsal blood vessels [16].

Trachomatis scarring (TS)

The presence of easily visible scarring in the upper tarsal conjunctiva [16].

Trachomatis trichiasis (TT)

The presence of at least one eyelash rubs on the eyeball or evidence of removal of in-turned eyelashes in the two weeks before examination [16].

Corneal opacity (CO)

the presence of easily visible corneal opacity over the pupil [16].

Exclusion and inclusion criteria

All the children belong to the appropriate age range mentioned above and who had lived in the district for at least 6 months, who were resident in selected villages and available at the time of study were invited to be included. Children who were seriously ill or for whom informed consent was not given by parents or guardians were excluded.

Measurements

The outcome variable was active trachoma and measured by physical examination. A number of dependent variables were considered that includes socio-demographic, environmental, hygiene and sanitation, and children’s demographic data.

Data collection tools and procedures

In collecting the data, face to face interviews, observation using a checklist and clinical eye examination were used. Experienced health informatics professionals were using structured interview questions that prepared from pieces of literature ( [17, 18], and Additional file 1), while they collected the data on a socio-demographic status, environmental, and housing conditions. All the questionnaires of socio-demographic status, housing, and environmental condition, observation checklist, and eye examination tools were pretested and validated before data collection in Kosomender, Meket district, a district bordering Wadla to the north. A household wealth index was developed using composite indicators for rural residents’ assets: livestock ownership, size of agricultural land and quantity of crop production. Two integrated eye care workers performed the eye examination. Those integrated eye care workers are ophthalmic nurses who had been previously trained for a total duration of one month for the purposes of contributing to the 2013–2014national trachoma survey. The Carter Center delivered that previous training using both pictures and live patients as media of instruction. However, for the purpose of this study, the trachoma graders undertook refreshment training for 5 days. This training considers examination of58 live patients and 100 pictures of different trachoma signs. Trainers, whose grades were used as the gold-standard assessment assessed graders. The training was also delivered for interviewers. Interviewers assisted graders by recording clinical grades, and data related to each household’s socio-demographic status and environmental situation. The trainers emphasized on the objectives, procedures of data collection and mode of communication between graders and interviewers. When undertaking the fieldwork, graders initially observed the eyelashes and cornea of study subjects, looking for TT and CO, then everted the upper lid and inspected the upper tarsal conjunctiva for TF, TI, or TS. Binocular lenses (× 2.5) and penlight torches were used [4] to magnify the examined eye.

Data analysis and presentation

The data were checked for completeness, coded and entered into Epi-info version 7, and transferred to SPSS version 23 for analysis. The data were checked for normality using Hosmer-Lemeshow-goodness-of-fit. A univariate analysis model were carried out, and variables that had a p-value of < 0.25 in a binary logistic regression model were included to the multivariate logistic regression analysis. Potential co-linearity was also considered and tested using multi co-linearity model in considering tolerance and variance inflection factor (VIF). Variables with a p-value of < 0.05 in the multivariate logistic regression analysis were considered as statistically significant. A principal component analysis was performed to categorize households’ wealth into poorer, poorest, middle, richer, and richest. However, for the presentation of the variables, the wealth index was grouped into three; lowest, middle, and highest. The procedure of eye examination and result reporting presented in Fig. 2. Both active trachoma and cicatricial trachoma were modeled as outcome variables. Thus, children were screened for both Active and cicatricial types of trachoma (Fig. 2).
Fig. 2

: The schematic presentation of eye examination outcome and result reporting procedure of active trachoma among rural preschool children in Wadla district, northern Ethiopia, 2017.

: The schematic presentation of eye examination outcome and result reporting procedure of active trachoma among rural preschool children in Wadla district, northern Ethiopia, 2017.

Data quality assurance

The questionnaire was prepared in English and translated to Amharic, then re-translated to English (to check for accuracy) by individuals, who are fluent in both English and Amharic. Both graders and one of the researchers, principal investigator had been participated in a community-based trachoma survey and training before starting the present study. The interviewers had also previous experience in a community-based data collection.

Results

In the study villages, there were 610 preschool children from 499 households. However, only 596 preschool children were examined and gave a response rate of 100%. The remaining 14 children were not involved in the screening phase because of the exclusion criteria and absenteeism after repeated household visit. More than three-fourths 383(77%) of households had male heads. The range in the number of residents per household was 2 to 10 with a median of five. The range in the number of 1 to 5 years old children per household was 1 to 3 with a median of one. All the 499 families were Amhara in ethnicity and followed Ethiopian orthodox Christianity, and 325 (65%) fathers, and 380 (76%) mothers were unable to read and write. Four hundred and sixty-six (93%) fathers were farmers and 16 (3%) fathers were government employees (Table 1).
Table 1

Socio-demographic characteristics of heads of households in rural Wadla district, northern Ethiopia, 2017

VariablesFrequency (n = 499)Percent (%)
Sex of head of a household
 Male38376.8
 Female11623.2
Marital status of head of a household
 Married49298.6
 Divorce71.4
Wealth index
 Poor14428.9
 Medium27955.9
 Rich7615.2
Occupation of head of a household
 Farmer46693.4
 Merchant173.4
 Government employee163.2
Educational status of head of a household
 Unable to read and write32565.1
 Able to read and write10921.8
 Up to grade 8357
 Grade 9 to 12193.8
 Diploma and above112.2
Educational status of mothers
 Unable to read and write38076.2
 Able to read and write5511
 Up to grade 8234.6
 Grade 9 to 12357
 Diploma61.2
Number of rooms in the house (observation)
 One42485
 Two and more7515
 Family size
 Less than 628657.3
 Greater than and equal to 621342.7
Total number of children less than five years in a house
 One42485
 Two6913.8
 Three61.2
Number of children less than ten years in a house
 One13226.5
 Two24048.1
 Three10220.4
 Four255
Adult face washing habit (self-report)
 At least one times per a day41783.6
 Less than 7 times per a week8216.4

In addition to the socio-demographic characteristics, the environmental characteristics of households are shown in Table 2.

Socio-demographic characteristics of heads of households in rural Wadla district, northern Ethiopia, 2017 In addition to the socio-demographic characteristics, the environmental characteristics of households are shown in Table 2.
Table 2

Environmental conditions of the study households in rural Wadla district, northern Ethiopia, 2017

VariablesFrequency (n = 499)Percent (%)
Presence of fly in or around a house (observation)
 Present24248.5
 Absent25751.5
Source of water (self-report)
 River306.0
 Unprotected well122.4
 Protected well5611.2
 Pipe40180.4
Amount of water in a litter (self -report)
 Less than 2018036.1
 20–4016232.5
 40–609218.4
 60–80499.8
Greater than 80163.2
 Total time taken to reach to water source (self-report)
 Less than and equal to 1/2 h.45992
 Greater than 1/2 h.408
Place of cooking (observation)
 In the same room of living house15731.7
 In the same house but in a kitchen16633.3
 A kitchen constructed against outside wall of the house3.6
 Isolated kitchen17334.7
Presence of window in a kitchen (observation)
 Yes24849.7
 No25150.3
Household waste removal (self-report)
 Burn it31262.5
 Bury it9018
 Dispose in the farm9318.8
 Dispose in another place4.8
Presence of latrine (observation)
 Present37174.3
 Absent12825.7
Presence of feces at open field in nearby a house (observation)
 Present24348.7
 Absent25651.3
Presence of cattle in a household (observation)
 Present43987.9
 Absent6012.1
Cattle sheltering (n = 439) (observation)
 In the same room where family lives12829.1
 In the same living house but in a separate room20346.2
 Attached shelter against outside of the house61.6
 Isolated shelter far from the house10223.1

Among children examined for signs of active trachoma, 301 (51%) were males, and 295 (49%) were females. The median age of children was 36 months (Table 3).

Environmental conditions of the study households in rural Wadla district, northern Ethiopia, 2017 Among children examined for signs of active trachoma, 301 (51%) were males, and 295 (49%) were females. The median age of children was 36 months (Table 3).
Table 3

Socio-demographic characteristics of the pre-school children in rural Wadla district, northern Ethiopia, 2017

VariablesFrequency (n = 596)Percent
Sex of children
 Male30150.5
 Female29549.5
Age of children in months (kebele registration book)
 12–2420834.9
 25–3610217.10
 37–4812921.6
 49–5915726.3
Current breast-feeding status of children
 Yes23940.1
 No35759.9
Face washing frequency of children (self-report)
 2 or more times per a day10818.1
 Once daily7913.3
 2 to 6 times per week14925
 Once weekly16728
 Stays unwashed for longer than a week.9315.6
Habit of child bathing for at least one times per a week (self-report)
 Yes44574.7
 No15125.3
Use of soap for face washing(self-report)
 Yes26444.3
 No33255.7
Use of soap for hand washing(self-report)
 Yes25442.6
 No34257.4
Face of children on observation (observation)
 Clean face28047
 Ocular discharge8914.9
 Nasal discharge7512.6
 Flies on the face of child10.6
 Ocular and nasal discharge345.7
 Ocular and nasal discharge and flies on the face559.2
Presence of another eye problem(self-report)
 Yes14624.5
 No45075.5
Type of eye problem (n = 146)
 Discharge9665.6
 Itching85.3
 Excessive tear2517.1
 Redness of eye1812.2
Took drug during mass drug administration in the last year(self-report)
 Yes51586.4
 No8113.6

Of the 596 screened children for signs of trachoma, 56.2% of female children had trachoma. One hundred and thirty children had active trachoma, giving a prevalence of 22% [95%CI, 18–25%)]. One hundred and six children had TF, 13 had TI, and 11 had both TF and TI. There were no signs of TS, TT or CO. Two hundred and eighty (47%) children had clean face, 89 (15%) had ocular discharge, 75 (13%) had nasal discharge, 34 (6%) had both ocular and nasal discharge and 55 (9%) children had nasal discharge, ocular discharge, and fly on their face.

Factors associated with active trachoma

On binary logistic regression analysis, lowest economic status, being in the age group of 24–36 months old, unable to read and write educational status of fathers, unable to read and write educational status of mothers, living in a house with a thatched grass roof, fly in a house, and a MUAC of children < 13.9 cm associated with active trachoma (Table 4). However, on the multivariable logistic regression analysis, only lowest economic status (AOR (95% CI), (3.80 (1.27–11.42)), being 37–48 months old (4.21 (1.47–12.03)), living in a house with a thatched grass roof (4.40 (1.42–13.59)), or presence of fly in a home (4.6 (2.1–9.9)) were increasing the odds of active trachoma (Table 4).
Table 4

Association of active trachoma and risk factors among pre-school children in rural Wadla district, northern Ethiopia, 2017

VariablesTrachoma (n = 596)OR (95% CI)
Presence (%)Absence (%)CORAOR
Type of house roof (observation)
 Clean iron15 (11.5)82 (17.6)1.001.00
 Thatch iron24 (18.5)141 (30.3)0.9(0.5–1.9)0.9 (0.3–2.8)
 Clean grass27 (20.8)144 (30.9)1.0(0.5–2.0)0.7 (0.2–2.2)
 Thatch grass64 (49.2)99 (21.2)3.5 (1.9–6.7) *4.4 (1.4–13.6) *
Fly in a house or in nearby (observation)
 Yes96(73.8)206 (44.2)3.6 (2.3–5.5)4.6 (2.1–9.9) *
 No34 (26.2)260 (55.8)1.001.00
Face washing frequency (self-report)
 Two and more times9 (6.9)99 (21.2)1.001.00
 Once daily2 (1.5)77 (16.5)0.3 (0.1–1.4)0.2 (0.03–1.3)
 2 to 6 times per a week15 (11.5)134 (28.8)1.2 (0.5–2.9)1.366 (.365–5.114)
 Once weekly63 (48.5)104 (22.3)6.7 (3.1–14.1) *8.7 (2.6–29.3) *
 Unwashed for a week41(31.5)52 (11.2)8.7 (3.9–19.2) *10.6 (2.9–37.7) *
Soap for face washing(self-report)
 Used26 (20)238 (51.1)1.001.00
 Not used104 (80)228 (48.9)4.2 (2.6–6.7) *>4.5 (1.8–11.3) *
Soap for hand washing(self-report)
 Used35 (26.9)219 (47.0)1.001.00
 Not used95(73.1)247 (53.0)2.4 (1.6–3.7) *1.6 (0.8–3.6)
Household latrine (observation)
 Present7 (21.2)364 (78.1)1.001.00
 Absent26 (78.8)102 (21.9)2.0 (1.3–3.0) *5.0 (2.0–12.9) *
Household waste around the house (observation)
 Exist80(61.5)214 (45.9)1.9 (1.3–2.8) *3.4 (1.6–7.6) *
 Not exist50 (38.5)252 (54.1)1.001.00
Mothers educational status
 Unable to read and write111 (85.4)348 (74.7)2.9 (1.3–6.6) *0.8 (0.2–3.2)
 Able to read and write12 (9.2)53 (11.4)2.1 (0.8–5.7)0.3 (0.1–1.6)
 Attend formal education7 (5.4)65 (13.9)1.001.00
Wealth index
 Poor73 (56.2%)101 (21.7)4.6 (2.3–9.1) *4.2 (1.5–12.0)
 Medium45 (34.6%)288 (61.8)1.003 (.506–1.988)0.5(0.2–1.4)
 Rich12 (9.2%)77(16.5)1.0001.00
MUAC of children
 Less than 13.981(62.3)230 (49.4)1.7 (1.1–2.52) *1.3 (0.6–2.6)
 Greater than 1449(37.7)236 (50.6)1.001.00
Age of children (in months)
 12–2442 (32.3)166 (35.6)0.8 (0.5–1.3)0.7 (0.3–1.8)
 25–3614 (10.8)88 (18.9)0.5 (0.3–0.9) *0.7(0.2–2.1)
 37–4836 (27.7)93 (20)1.2 (0.7–2.1)2.7(.1.0–7.2)
 49–5938 (29.2)119 (25.5)1,001.00
Fathers education
 Unable to read and write93 (71.5)299 (64.2)2.3 (1.1–4.7) *1.4 (0.3–6.2)
 Able to read and write28 (21.5)102 (21.9)1.9(0.9–4.5)2.1 (0.5–9.7)
 Formal education9 (6.9)65 (13.9)1.001.00

* = p < 0.05

Socio-demographic characteristics of the pre-school children in rural Wadla district, northern Ethiopia, 2017 Of the 596 screened children for signs of trachoma, 56.2% of female children had trachoma. One hundred and thirty children had active trachoma, giving a prevalence of 22% [95%CI, 18–25%)]. One hundred and six children had TF, 13 had TI, and 11 had both TF and TI. There were no signs of TS, TT or CO. Two hundred and eighty (47%) children had clean face, 89 (15%) had ocular discharge, 75 (13%) had nasal discharge, 34 (6%) had both ocular and nasal discharge and 55 (9%) children had nasal discharge, ocular discharge, and fly on their face. Association of active trachoma and risk factors among pre-school children in rural Wadla district, northern Ethiopia, 2017 * = p < 0.05

Discussion

The objective of this study was to assess the current prevalence of active trachoma and to identify its associations among children aged 1 to 5 years old in rural communities of Wadla district. The prevalence of active trachoma in this age group was 22%, [95%CI, 18–25%], whereas the prevalence of TF was 21%. Although the usual indicator age group for determining the need or otherwise for the A, F and E components of the SAFE strategy is the prevalence of TF in 1 to 9 years-old children, the prevalence that we estimate here suggests that three further years of antibiotic mass drug administration is likely to be required, according to WHO recommendation [19]. However, a study from northern Ethiopia reported that azithromycin mass treatment coverage in 2012 was 92.9% [20]. That reported mass azithromycin coverage was greater than the minimum coverage set by WHO, 80% [21]. The prevalence agreed with a review that indicated 70 million people in Ethiopia required MDA. This was the largest need of any other country in the world [22]. The prevalence of TI among 1 to 5 years old children here was 3.4%. Severe inflammatory trachoma is a risk factor for later cicatricial disease, particularly when the sign is observed repeatedly over a time [23]. In our subjects, reportedly face washing once weekly and having a face that had remained unwashed for longer than a week were associated with active trachoma. Similar associations had been seen elsewhere [18, 24]. We also found that the absence of a toilet or presence of human excreta near to a home increased the odds of there being active trachoma. Recent multi-country observational data support the link between inadequate access to sanitation and the likelihood of active trachoma [25]. In general, the associations that we found agreed with the previous published literature that suggests a strong links between trachoma and environmental factors related to water, sanitation, and hygiene. Some of these associations implicate the fly Muscasorbens, which oviposit in human excreta left exposed on the soil, as an important vector [26-28]. In this study, grassed and thatched house roof (AOR (95% CI), 4.402 (1.425–13.597) were increasing the odds of active trachoma. This association evidenced from central Ethiopia [29].In this study, not using soap was increasing the odds of active trachoma [(AOR (95%CI), 4.49 (1.79–11.29)]. This agreed with studies that were conducted in Dessie city and Gonder, Ethiopia [13, 30]. Unfortunately, we did not have any entomological data for this site. Other limitations of our analyses include our reliance on self-report for many of the exposure variables, and the exclusion of children aged 6 to 9 years old. However, this research estimates the prevalence of active trachoma among preschool children from rural area, and its associations, for the attention of policymakers interested in trachoma elimination in Wadala district, Amhara region, Ethiopia.

Conclusions

The prevalence of active trachoma among rural preschool children in Wadla district was high, suggesting that active trachoma is still a public health problem in Wadla district. Environmental factors were found to be associated with active trachoma. This might suggest an ongoing need for implementation of the F and E components of the SAFE strategy for trachoma elimination in this district to prevent future trachomatis blindness. Additional file 1.
  17 in total

1.  Progression of active trachoma to scarring in a cohort of Tanzanian children.

Authors:  S K West; B Muñoz; H Mkocha; Y H Hsieh; M C Lynch
Journal:  Ophthalmic Epidemiol       Date:  2001-07       Impact factor: 1.648

2.  A simple system for the assessment of trachoma and its complications.

Authors:  B Thylefors; C R Dawson; B R Jones; S K West; H R Taylor
Journal:  Bull World Health Organ       Date:  1987       Impact factor: 9.408

3.  Human and other faeces as breeding media of the trachoma vector Musca sorbens.

Authors:  P M Emerson; R L Bailey; G E Walraven; S W Lindsay
Journal:  Med Vet Entomol       Date:  2001-09       Impact factor: 2.739

4.  Strategies for control of trachoma: observational study with quantitative PCR.

Authors:  Anthony W Solomon; Martin J Holland; Matthew J Burton; Sheila K West; Neal D E Alexander; Aura Aguirre; Patrick A Massae; Harran Mkocha; Beatriz Muñoz; Gordon J Johnson; Rosanna W Peeling; Robin L Bailey; Allen Foster; David C W Mabey
Journal:  Lancet       Date:  2003-07-19       Impact factor: 79.321

5.  Effect of 3 years of SAFE (surgery, antibiotics, facial cleanliness, and environmental change) strategy for trachoma control in southern Sudan: a cross-sectional study.

Authors:  Jeremiah Ngondi; Alice Onsarigo; Fiona Matthews; Mark Reacher; Carol Brayne; Samson Baba; Anthony W Solomon; James Zingeser; Paul M Emerson
Journal:  Lancet       Date:  2006-08-12       Impact factor: 79.321

6.  Spatial clustering of high load ocular Chlamydia trachomatis infection in trachoma: a cross-sectional population-based study.

Authors:  Anna Last; Sarah Burr; Neal Alexander; Emma Harding-Esch; Chrissy H Roberts; Meno Nabicassa; Eunice Teixeira da Silva Cassama; David Mabey; Martin Holland; Robin Bailey
Journal:  Pathog Dis       Date:  2017-07-31       Impact factor: 3.166

7.  Sanitation and water supply coverage thresholds associated with active trachoma: Modeling cross-sectional data from 13 countries.

Authors:  Joshua V Garn; Sophie Boisson; Rebecca Willis; Ana Bakhtiari; Tawfik Al-Khatib; Khaled Amer; Wilfrid Batcho; Paul Courtright; Michael Dejene; Andre Goepogui; Khumbo Kalua; Biruck Kebede; Colin K Macleod; Kouakou IIunga Marie Madeleine; Mariamo Saide Abdala Mbofana; Caleb Mpyet; Jean Ndjemba; Nicholas Olobio; Alexandre L Pavluck; Oliver Sokana; Khamphoua Southisombath; Fasihah Taleo; Anthony W Solomon; Matthew C Freeman
Journal:  PLoS Negl Trop Dis       Date:  2018-01-22

8.  Detecting extra-ocular Chlamydia trachomatis in a trachoma-endemic community in Ethiopia: Identifying potential routes of transmission.

Authors:  Anna Last; Bart Versteeg; Oumer Shafi Abdurahman; Ailie Robinson; Gebeyehu Dumessa; Muluadam Abraham Aga; Gemechu Shumi Bejiga; Nebiyu Negussu; Katie Greenland; Alexandra Czerniewska; Nicholas Thomson; Sandy Cairncross; Virginia Sarah; David Macleod; Anthony W Solomon; James Logan; Matthew J Burton
Journal:  PLoS Negl Trop Dis       Date:  2020-03-04

9.  Association between water related factors and active trachoma in Hai district, Northern Tanzania.

Authors:  Michael J Mahande; Humphrey D Mazigo; Eliningaya J Kweka
Journal:  Infect Dis Poverty       Date:  2012-11-01       Impact factor: 4.520

10.  Trachoma and Relative Poverty: A Case-Control Study.

Authors:  Esmael Habtamu; Tariku Wondie; Sintayehu Aweke; Zerihun Tadesse; Mulat Zerihun; Zebideru Zewdie; Kelly Callahan; Paul M Emerson; Hannah Kuper; Robin L Bailey; David C W Mabey; Saul N Rajak; Sarah Polack; Helen A Weiss; Matthew J Burton
Journal:  PLoS Negl Trop Dis       Date:  2015-11-23
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