Health and economic burden of foodborne zoonotic diseases in Amhara region, Ethiopia.

Diseases from food of animal origin are common health problems in Ethiopia. A cross-sectional study was carried out to estimate health and economic burden, and to identify demographic factors associated with community awareness of foodborne zoonotic diseases in Amhara region, Ethiopia. Data was collected from 435 households in three towns: Gondar, Lalibela and Debark. A retrospective data was also collected from health records in each town. The health burden due to zoonotic diseases was estimated at 0.2, 0.1 and 1.3 DALYs per household per year and at 73.2, 146.6 and 1,689.5 DALYs out of 100,000 populations per year in Gondar, Lalibela and Debark, respectively. The overall health burden due to foodborne zoonotic diseases (aggregated over the 435 households in the three towns) was estimated to be 89.9 DALYs per 100,000 populations per year. The economic impact of foodborne zoonotic diseases in the three towns of Amhara regional state was 278.98 Ethiopian Birr (ETB) (1ETB = 0.025 US Dollar) per household per year and 121,355.68 ETB per year. Costs of preventive measures followed by costs of patients' time made the highest contribution while costs of diagnosis made the lowest contribution to the total economic burden of foodborne zoonotic diseases. From a total of 435 respondents, 305 (70.1%) had known the presence of zoonotic diseases. Level of education, number of families in the house and income were highly associated with awareness of zoonosis. Although majority of respondents had known zoonotic diseases exists (70.1%) and disease can be acquired from animal source food (63.2%), the health and economic burden associated to foodborne zoonotic diseases are still high. Therefore, changing mindset and practical training aiming in controlling foodborne zoonotic diseases may be suggested to the community in the health improvement extension service.

1. Introduction

Zoonotic diseases are diseases transmissible between people and animals. Nearly two-thirds of human infectious diseases exerting heavy public health and economic burden to the global community originate from animals [1, 2]. In the absence of proper care of the relation between animal and human populations, zoonotic diseases can lead to a serious risk of public health with huge economic consequences [3]. Zoonotic diseases threaten the health and productivity of animals, the livelihood of people, and cause illness and death in consumers [4]. Worldwide, the direct cost of zoonotic diseases over the last decade has been estimated to be more than $20 billion with over $200 billion indirect losses [5]. Zoonotic diseases and diseases recently emerged from animals have been estimated to contribute more than a quarter of the disability-adjusted life years (DALYs) lost to infectious diseases in low income countries such as sub-Saharan Africa [6]. In these countries, however, the economic and health burden associated to zoonotic disease is often given low attention and is largely unknown [4]. In order to obtain a better understanding of their health impact, calculating summary measures of population health such as the DALY is necessary. The attention given to zoonotic diseases has however focused more on emerging zoonotic diseases that pose global economic and health threats than endemic zoonotic diseases [7-9]. Quantitative data on health and economic burden of zoonotic diseases may contribute in changing mindset to make informed decision on prevention and control of endemic zoonotic diseases.

Foodborne diseases have enormous impacts on the health and livelihoods of people around the globe and are of great concern to consumers, producers, and policymakers. Although many articles have been published on (foodborne) zoonotic diseases worldwide [10-14]), specific information on health and economic impact of (foodborne) zoonotic diseases in developing countries is limited [4]. So, in order to get a better understanding of the impacts of zoonotic diseases specifically for the situation in developing countries, estimates of the health and economic burden of foodborne zoonotic diseases are needed. By estimating the burden of foodborne zoonotic diseases, awareness of the economic and health consequences of these diseases can be created, which is a first step for prevention and an important part of motivating policy makers to take preventive measures against foodborne zoonotic diseases. Particularly, the estimation of the burden of foodborne zoonotic diseases in households can be helpful, as it provides households with estimate to assess their own situation.

Ethiopia has the second largest human population in Africa and the largest in livestock population in the continent [15]. About 80% of Ethiopians are dependent on agriculture and have direct contact with livestock or other domestic animals which creates opportunity for infection and spread of zoonotic diseases between humans and animals [4]. This and having a large population of low income livestock farmers, Ethiopia also ranks very high in the health burden of zoonotic diseases [13]. The situation is very much pronounced in rural communities of Ethiopia where animals and humans share the same microenvironment including a shelter [16]. Besides, the handling and widespread habit of raw beef consumption in Ethiopia can favor the spread of foodborne zoonotic infection. Raw meat without appropriate temperature control is available in open-air in local retail shops for sale and minced meat, ‘Kitfo’ in Ethiopian Amharic language, is served as raw or under cooked at restaurants.

There are a lot of foodborne diseases in Ethiopia [4]. Salmonellosis is one of the most common foodborne bacterial zoonotic diseases identified from food animals in Ethiopia [17]. Non-typhoidal Salmonella represents an important human and animal pathogen worldwide [18]. In humans, in addition to concern about foodborne zoonotic diseases caused by Salmonella organisms, concern has also been raised about the impact of acquired antimicrobial resistance transferred among these organisms [19]. Listeriosis is an important emerging foodborne bacterial zoonotic infection worldwide. Ready-to-eat food-mediated listeriosis infection in humans has been documented by several workers from different parts of the world [20, 21]. In Ethiopia, Molla et al. [22] demonstrated widespread occurrence and distribution of L. monocytogenes and other Listeria species in retail meat and milk products in Addis Ababa. Despite the potential threat to human health posed by listeriosis, there is scarcity of data on the public health and economic burden associated to this disease. From, helminthes, taeniasis caused by Tinea saginata is common infection associated to eating raw or undercooked beef in many sections of human population in the country [23].

Relatively “many articles” are published on the epidemiology of foodborne zoonotic diseases in Ethiopia [4, 16, 24–31]. However, to our knowledge, there is no literature on the health and economic burden of foodborne zoonotic diseases [4]. The present study aimed at estimating the impact of foodborne zoonotic diseases on health and economy, and to identify factors associated with awareness of the people about these diseases in Amhara region, Ethiopia.

2. Materials and methods

2.1. Study area

The study was conducted in three towns selected from Amhara regional state: Gondar, Debark and Lalibela. These towns were selected because they are destinations for large number of tourists. The 2014–2017 projected populations, projection made based on the results of National population and Housing Census of Ethiopia conducted in May 2007, for the three towns were 306, 246 for Gondar, 30,781 for Debark and 27, 200 for Lalibela [32].

2.2. Study population and animal source food consumption habits

As there was no previous study that estimated health and economic burden of foodborne zoonotic diseases in Ethiopia, the sample size was not estimated based on previous study. The sample size was 435 households by our expertise estimate of representativeness and taking time and logistical considerations into account. This sample size was allocated proportional to the size of the households for each of the towns: 286 to Gondar, 71 to Lalibela, and 78 to Debark. Households were randomly selected and heads of households were approached; 435 heads of households who volunteered to participate in the study were included.

The studied households consume both cereals and animal products. Overall diets are dominated by grains and that both per capita consumption and food budget shares of animal source food are low. Nowadays, the quantity of animal source food consumption is increasing although the increase is modest because of relatively higher price of animal products. Consumption of animal source food is also seasonal. Orthodox Christians don’t consume animal source food during fasting season and on Wednesdays and Fridays except the 50 days running from Easter. Animal source food consumption peak is associated with major religious events [33]. No such seasonality is seen during the Muslims’ major fasting season of Ramadan. Both religious groups are dependent on limited types of animals for meats due to cultural taboo for some food animals such as pigs. The per capita consumption in towns is higher than the per capita consumption in rural areas linked to income differences and associated resulting changes in household preferences [34]. A cow or an ox is commonly butchered for the sole purpose of selling and most people buy raw meat from butchers and cook and consume within their home. In special occasions, people have a cultural ceremony of slaughtering cow or ox and sharing among the group. In addition to consuming completely or partly cooked meat, eating raw meat is a common practice. At the larger butcheries, many frequently sit and eat traditional meal of higher quality raw meat [35].

2.3. Design of the questionnaire and data collection

A questionnaire was prepared to collect data on demography, household health expenses, treatment service, time spent on seeking health service, and risks associated to diarrhea disease. Most of the questions were closed questions to make ease of the analysis. The original questionnaire was prepared in English and translated into local language (Amharic), and subsequently translated back into English by an external translator to validate the translation. The questionnaire was pilot-tested by administering to 5 people that have similar characteristics to the study participants outside the study. The questionnaire was corrected based on the response of the pilot test. The English version of the questionnaire is provided in S1 Questionnaire.

The questionnaire was administered by face-to-face interviews to the 435 respondents recruited from the study towns. In addition, a retrospective data was collected from records of health centers serving the study towns. In the retrospective data collection, cases with signs of diarrhea referred for laboratory confirmation in the last two years were sought from patient records of two health centers in each of the three towns. In accordance with the local legislation and institutional requirements, ethical review and approval was not required for such questionnaire study. A verbal informed consent was obtained from respondents before the start of the interview and the data was analyzed and reported anonymously.

2.4. Data management and analysis

The health and economic impact of foodborne zoonotic diseases was estimated based on the number of cases of diarrhea obtained from respondents and the proportion of diarrhea case caused by foodborne zoonotic diseases obtained from health center records. The proportion of diarrhea cases caused by foodborne zoonotic diseases (0.49) derived by dividing the number of diarrhea caused due to confirmed foodborne zoonotic diseases (653) to the total number of diarrheic cases confirmed by laboratory (1332) in the last one year. As respondents were not willing to tell their household size, average household size of 4.8 for the region was used from secondary sources [36]. Data used to estimate the impact of foodborne zoonotic diseases on health and economy and to identify factors associated with awareness of the people about these diseases in Amhara region, Ethiopia are available in S1 Table.

2.5. Calculation of impacts of foodborne zoonotic diseases on health

Health impact of foodborne zoonotic diseases was estimated by summary disease measure of disability adjusted life years (DALY) which is sum of years of life lost (YLL) due to premature mortality and years lived with disability (YLD) [37, 38].

Years of life lost

Years of life lost due to death associated to foodborne zoonotic diseases was estimated from expected years of life lost at death derived from the standard life table for Ethiopia as given by WHO and from the number of deaths due to foodborne zoonotic diseases as

Where

YLL = Years of life lost due to death associated with foodborne zoonotic disease in household with age i

= Number of human death in household with age i

E = Life expectancy of the concerned category of age i

Years lived with disability

Years lived with disability was estimated separately for disability due to the diseases and due to the medication.

Years lived with disability due to diarrhea

Years lived with disability due to foodborne zoonotic disease associated diarrhea was estimated from number of diarrheic patients, average duration of stay with the diarrhea and disability weight of 0.17 for diarrhea, averaged from the disability report for mild, moderate and sever cases of diarrhea from Salomon et al. [39] as

Where:

YLD = Years lived with disability due to foodborne zoonotic disease associated diarrhea in household

N = Number of diarrheic patients in household

T = Average duration of stay with diarrhea associated to the foodborne zoonotic diseases in household

DW = Disability weight of diarrhea

Years lived with disability due to medication

This was estimated from the number of patients treated for foodborne zoonotic diseases associated diarrhea, average duration of treatment and disability weight of medication. Disability weight of 0.07 for daily medication for generic uncomplicated diseases estimated by Haagsma et al. [40] was used.

Where:

YLD = Years lived with disability due to medication of diarrhea associated with foodborne zoonotic disease in household i

= Number of patients treated for diarrhea associated with foodborne zoonotic diseases in household i

T = Average duration of treatment of with diarrhea associated to the foodborne zoonotic diseases in household i

DW = Disability weight of medication from the literature for generic uncomplicated diseases

Total DALYs in household was the summation of years of life lost due to death, years lived with disability due to the diseases and years lived with disability due to medication of diarrhea associated to foodborne zoonotic diseases as

Where:

YLL = Years of life lost due to death associated to foodborne zoonotic disease of individual with age i

YLD = Years lived with disability due to foodborne zoonotic disease associated diarrhea

YLD = Years lived with disability due to medication associated to foodborne zoonotic disease associated diarrhea

2.6. Estimating economic impacts of foodborne zoonotic diseases

The economic impact of foodborne zoonotic diseases for study participant households was aggregated from the cost of diagnosis, cost of drug, cost of informal care takers and cost of patients’ time per year. Economic impact due to illness falls into two broad categories, namely direct and indirect costs. Direct costs are costs incurred for health care services such as costs of diagnosis and costs for drugs. Indirect costs are opportunity costs due to productive working time losses resulting from illness and to other healthy members of household [41].

Costs of diagnosis of foodborne zoonotic diseases

Where:

= Costs of diagnosis of foodborne zoonotic diseases in household i

= Number of patients treated for foodborne zoonotic disease in household i

= Price of diagnosis per case in household i

Costs of drugs

Where:

= Costs of drug to treat a case associated to foodborne zoonotic disease in household i

= Number of patients treated for foodborne zoonotic disease in household i

= Price of drug per case in household i

Costs of informal care takers

Where:

= Costs of informal care takers in household i

= Number of patients treated for foodborne zoonotic disease in household i

= Time taken by informal care takers to nurse a patient in household i

= Price of labor per hour (25 Ethiopian Birr) in Amhara region. The official exchange rate during the study year was One ETB for 0.025 USD.

Costs of patients’ time

Where:

= Costs of patients’ time associated to illness in household i

= Number of patients treated for foodborne zoonotic disease in household i

= Productive working time losses resulting from illness and treatment in patients treated in household i

= Number of patients untreated for foodborne zoonotic disease in household i

= Productive working time losses resulting from illness in patients untreated in household i

= Price of labor per hour (25 Ethiopian Birr) in Amhara region

2.7. Analyzing factors associated with awareness of foodborne zoonotic diseases

Descriptive statistics such as frequency distribution and percentages were used to summarize the data. Factors associated with awareness of foodborne zoonotic diseases were analyzed using logistic regression. The dependent binary variable was awareness of foodborne zoonotic disease (yes or no). Independent variables were study town (Gondar, Lalibela and Debark), gender (male and female), household size (one person or >one person), age in years (<35, >35 to 50 and >50), level of education (illiterate, general education, college education), and income per month (<2500 Ethiopian Birr (ETB), 2501–5000 ETB, 5001–7500 ETB and >7500 ETB.

Independent variables were screened using univariable logistic regression. Pair-wise correlations between independent variables were evaluated using the Spearman Rank correlations for variables significant in the univariable analysis. If two variables had a correlation coefficient of ≥0.7, only one of the variables was included in the multivariable analysis. Variables statistically significant at P < 0.05 in the univariable analyses were tested starting from the full model by removing one variable at a time in the same multivariable logistic regression models using backward reduction. Variables in multivariable models with P < 0.05 from the Wald test were retained. All two-way interactions between variables in the final multivariable models were tested. Confounding was checked during the model building process by evaluating the change in the coefficients of other variables when a variable was eliminated from the models. If this change in beta estimate was >30%, the variable was considered a confounder. The analyses were done using Stata statistical software release 14 (Stata Corp LLC, USA).

3. Results

Majority of respondents, 298 (68.5%) were males. The youngest and the oldest age of the respondents were 11 and 66 years, respectively while their average age was 40 years. Majority of respondents, 355 (81.6%) attended college education while 26 of them were illiterate, and 54 attended general education. Majority of households 265 (61%) had more than one person in the household while 170 of households had one person in the household.

3.1. Health and economic burden of foodborne zoonotic diseases

The health and economic impact estimates were based on three diarrhea causing foodborne zoonotic diseases: salmonellosis, listeriosis and taeniasis which were confirmed in health centers of the three towns: Gondar, Lalibela and Debark in North West Ethiopia. The minimum, average and maximum values of the most important input items for the health and economic impact estimate are summarized in Table 1.

Table 1

Summary of the minimum, average and maximum annual values of parameters used in estimating health and economic burden of foodborne zoonotic diseases (N = 435).

Model parameters	Minimum	Average	Maximum
Number of diarrheic patients per household	1	1.5	3
Number of patients treated per household	0	0.9	2
Costs of diagnosis (ETB1)	5	36.4	350
Costs of treatment and drug (ETB)	20	82	500
Duration of treatment (days)	0	1.7	9
Sick leave time (days)	0	4.2	33
Waiting for diagnosis (hours)	0	3.2	12
Time taken of informal care takers (days)	0	0.7	6
Number of dead people per household	0	0.03	1
Age of death of individuals (years)	0	0.08	5
Days elapsed before seeking treatment (Days)	0	2.24	7
Costs of prevention of diarrhea (ETB)	0	431	3,000

1Ethiopian Birr.

An average annual human mortality rate of 0.01 was recorded associated to foodborne zoonotic diseases. The minimum, average and maximum income of respondents were 500 ETB, 4,652.6 ETB and 12,000 ETB, respectively. Eighteen percent of households did not visit health centers to seek treatment for diarrhea. Costs of diagnosis, costs of treatment and drug, and costs of prevention of diarrhea varied largely between households.

3.2. Public health burden of foodborne zoonotic diseases

Based on the number of respondents in each of the towns, the health burden due to foodborne zoonotic diseases in Gondar, Lalibela and Debark towns were 0.2, 0.1 and 1.3 DALYs per household per year, respectively. Further, the health burden was estimated at 73.2, 146.6 and 1,689.5 DALYs out of 100,000 populations per year in Gondar, Lalibela and Debark towns, respectively. The overall health burden due to foodborne zoonotic diseases (aggregated over the 435 households in the three towns) was estimated to be 89.9 DALYs per 100,000 populations per year (Table 2).

Table 2

Annual health burden due to foodborne zoonotic diseases in disability adjusted life years per 100,000 population in Gondar, Lalibela and Debark towns in Amhara region, Ethiopia.

Source of health burden	Gondar	Lalibela	Debark	Overall
Years of life lost	38.9	0	1,530.2	66
Disability due to medication	6.5	37.5	23.7	4.6
Disability due to foodborne associated diarrhea	27.8	109.1	135.6	19.3
Total DALY1	73.2	146.6	1,689.5	89.9

1Disability adjusted life years.

3.3. Economic impact of foodborne zoonotic diseases

The economic impact of foodborne zoonotic diseases in the three towns of Amhara regional state, in average, was 278.98 ETB per household per year. The overall economic burden due to foodborne zoonotic diseases (aggregated over the 435 households in the three towns) was estimated to be 121,355.68 ETB per year. Of the different cost factors, costs of preventive measures’ made the highest contribution while costs of diagnosis made the lowest contribution to the total economic impact of foodborne zoonotic diseases (Table 3).

Table 3

Economic impact of foodborne zoonotic diseases on health based on selected households in the community (N = 435).

Costs	Cost factors	Gondar	Lalibela	Debark	Total
Direct Costs	Costs of diagnosis	6,240.64	857.5	1,249.5	8,347.64
	Costs of drugs	6,803.16	1,964.9	3,964.1	12,732.16
Indirect costs	CPWTL1	15,000.13	3,356.50	4,814.25	23,170.88
	Costs of informal care takers	6,750	2,145	500	9,395
Costs of preventive measures		57,950	2,910	6850	67,710
Total economic impact		92,743.93	11,233.90	17,377.85	121,355.68

1Costs of productive working time losses.

3.4. Awareness of foodborne zoonotic diseases

From a total of 435 respondents, 305 (70.1%) knew the presence of zoonotic diseases and 275 (90%) of them knew zoonotic diseases can be acquired from food. The awareness that zoonosis can be acquired from food was highest in Debark and it is more in men than in women and this awareness decreased with increased age of respondents. On the other hand the awareness about foodborne zoonotic disease increased with increased the level of education and income. Table 4 summarizes awareness of foodborne zoonosis by different socio-demographic variables.

Table 4

Descriptive statistics showing awareness of foodborne zoonotic diseases and socio-demographic characteristics of study participants in Amhara region, Ethiopia.

Variable	Level	Number of respondents	Aware zoonosis can be acquired from food (%)
Study site	Gondar	286	176 (62)
	Lalibela	71	46 (65)
	Debark	78	53 (68)
Gender	Female	137	80 (58)
	Male	298	195 (65)
Age in years	<35	164	100 (61)
	36–50	201	134 (67)
	>50	70	41 (59)
Level of education	Illiterate	26	8 (31)
	General education	54	24 (44)
	College education	355	243 (68)
Household size	One person	170	87 (51)
	> one person	265	188 (71)
Income category in ETB1	< 2500	73	34 (47)
	2501–5000	195	111 (57)
	5001–7500	124	90 (73)
	>7500	43	40 (93)

1Ethiopian Birr

3.5. Socio-demographic factors associated with awareness of foodborne zoonotic diseases

Three variables were statistically significant association with awareness of foodborne zoonotic diseases. Table 5 summarizes univariable associations between awareness of foodborne zoonotic diseases and socio-demographic characteristics of respondents.

Table 5

Univariable associations between awareness of foodborne zoonotic diseases and socio-demographic characteristics of 435 respondents in Amhara region, Ethiopia.

Variable	Level	OR1	95% CI2	P-value
Study town	Gondar	Ref3
	Lalibela	1.15	(0.67–1.98)	0.613
	Debark	1.3	(0.78–2.25)	0.300
Gender	Female	Ref.
	Male	1.35	(0.89–2.04)	0.158
Age in years	<35	Ref.
	36–50	1.28	(0.83–1.97)	0.260
	>50	0.90	(0.51–1.60)	0.731
Level of education	Illiterate	Ref.
	High School	1.8	(0.67–4.85)	0.245
	Diploma and above	4.89	(2.06–11.56)	0.001
Household size	One person	Ref.
	>one person	2.33	(1.56–3.48)	0.001
Income	< 2500	Ref.
	2501–5000	1.52	(0.88–2.60)	0.131
	5001–7500	3.04	(1.66–5.57)	0.001
	>7500	15.29	(4.34–53.93)	0.001

1Odds ratio.

2Confidence interval.

3Reference.

Level of education, household size and income were statistically significant association with awareness by the multivariable logistic regression model. The final multivariable model is presented in Table 6.

Table 6

The final multivariable mixed models describing the associations between awareness of foodborne zoonotic diseases and respondents socio-demographic characteristics on 435 respondents in Amhara region, Ethiopia.

Variable	Level	OR1	95% CI2	P-value
Level of education	Illiterate	Ref3
	High School	2.30	(0.83–6.36)	0.108
	Diploma and above	5.17	(1.86–14.39)	0.002
Household size	One person	Ref.
	>one person	2.27	(1.48–3.49)	0.001
Income	< 2500	Ref.
	2501–5000	0.76	(0.38–1.530)	0.448
	5001–7500	1.24	(0.55–2.78)	0.600
	>7500	5.64	(1.43–22.32)	0.014

1Odds ratio.

2Confidence interval.

3Reference.

4. Discussion

The objectives of this study were to estimate impact of foodborne zoonotic diseases on health and economy and to assess demographic factors associated with awareness of foodborne zoonotic diseases in Amhara region, Ethiopia. One of the first prerequisites in making decision to implement measures to control foodborne zoonotic diseases is to perceive foodborne zoonotic diseases as a health burden and is an economic problem. Decision makers, however, do not always perceive foodborne zoonotic diseases as costly, and therefore underestimate these diseases as a problem. Although there are a reasonable number of papers on health burden and economic impact of foodborne zoonotic diseases in the literature, to our knowledge, there is no study so far which estimated the economic and health burden of foodborne zoonotic diseases in Ethiopia. Specifically for developing countries this type of knowledge, although valuable, is lacking. Of the 146 studies recently reviewed for major foodborne zoonotic bacterial pathogens, no study estimated the economic and health burden of foodborne zoonotic diseases in developing countries [31]. Through estimating economic and health burden of foodborne zoonotic diseases in Ethiopia, the current study shows the need of improving prevention of foodborne zoonotic diseases.

Decision makers are often unaware of the economic impacts of foodborne zoonotic diseases. Creating awareness on the health and economic burden of foodborne zoonotic diseases may be an important step, because people first have to consider foodborne zoonotic diseases as problem before they are motivated to take measure [42]. This may be helpful in their motivation to implement preventive measures that (partly) may have been known already, but that were considered to not be outweighing the problem to be solved. Thus giving more insight to the health and economic burden associated to foodborne zoonotic diseases may motivate households to change their behavior related to prevention of these diseases within their cultural framework for better community acceptance.

Collecting data on factors such as additional cost for better food for sick person and better care under the local circumstances was quite challenging. Disability weights for diarrhea and medication associated to foodborne zoonotic diseases were used from the literature. Since respondents didn’t know whether a disease affecting one or more of their household members was zoonotic, the response obtained in the questionnaire was extrapolated towards a whole year. Consequently, the number of foodborne zoonotic diseases was obtained based on extrapolating the data obtained in the questionnaire using confirmatory diagnosis from retrospective data in health records.

The economic impact of foodborne zoonotic diseases in three towns of Amhara region, in average, was 279 ETB per household per year. This means that it was equivalent to 0.5% of the average annual income of respondents. Besides the economic impacts described in this paper, there are additional costs associated to foodborne zoonotic diseases result from costs related to transport costs to travel to hospitals. However, this cost was not included as both patient and the care taker mostly walk to hospitals. This might have underestimated the economic impact of foodborne zoonotic diseases. In absolute terms, the economic impacts of foodborne zoonotic diseases estimated looks small but is significantly related to the average income of Ethiopian respondents. So the study indicated that foodborne zoonotic diseases are causing significant economic impact to households in the study area.

There was large variation in the economic impacts of foodborne zoonotic diseases between households. The largest part of the variation can be explained by differences in costs of preventive measures and in costs of treatment and drug. Although we wanted to base the estimate of economic impacts of foodborne zoonotic diseases as much as possible on actual confirmed data, it was not possible to retrieve all needed data from the field. Therefore we had to make a number of assumptions, for instance on costs of labor. Because of the assumption, there may be discrepancies between the real economic impacts of foodborne zoonotic diseases and our estimates. A relatively large part (52%) of the total economic impacts of foodborne zoonotic diseases was due to costs of preventive measures. However, as there is no any previous study, to our knowledge, it was not possible to compare. The contribution of costs of patients’ time to the total economic impacts of foodborne zoonotic diseases is caused by the long time taken for treatment, sick leave, and absenteeism from work because of the disease.

Larger majority of respondents (70.1%) had known the presence of zoonotic diseases but only a smaller majority (63.2%) knew disease can be acquired from food. Both findings were substantially lower than the earlier reported in and around Addis Ababa, Ethiopia [26] although the respondent of that study were elementary and high school students, and Graduates of which 33% were health professionals. Level of education, income and household size were associated with awareness of foodborne zoonotic diseases. This may be related to the fact that more level of education has direct relevance to awareness related health and diseases. Households with more than one person in a house had higher odds of awareness of foodborne zoonotic diseases than households of one person in a house. This one is explained from the fact that if more people live in the household, there is more chance that at least one of them be aware and transmits this awareness to other members of the household.

This study aimed to assess the burden of foodborne zoonotic diseases in Amhara region, Ethiopia in terms of DALYs. The estimates might not have been very accurate as cases were determined by extrapolation of few confirmed cases based on retrospective data. Moreover, we found that not all cases with diarrhea seek health service. As acknowledged by WHO [43], the high life expectancy allocated and the relatively higher number of cases and death to children result in higher DALYs of foodborne zoonotic diseases in these age groups. Extrapolation to the national scale can provide an indication of the health and economic burden associated to foodborne zoonotic diseases in the country. However, the estimate should be interpreted with caution, given the relative limited number of towns studied and the nature of the data.

5. Conclusions

Foodborne zoonotic diseases were associated with high health and economic burden in Amhara Region, Ethiopia. The overall health burden due to foodborne zoonotic diseases (aggregated over the 435 households in Gondar, Lalibela and Debark towns) was estimated to be 89.9 DALYs per 100,000 populations per year. On average, the economic burden was 278.98 ETB per household per year and show large variation between households. Relative to the income of households, these costs are high. The total costs of foodborne zoonotic diseases were mainly due to costs of preventive measures. Although further study is needed at some points, respondents socio-demographic characteristics associated with awareness of foodborne zoonotic diseases were identified, that can be helpful in tailoring control of foodborne zoonotic diseases in Amhara region, Ethiopia. Changing mindset and practical training aiming in controlling foodborne zoonotic diseases is suggested in the health improvement extension service.

Questionnaire on health and economic burden of foodborne zoonotic diseases.

(DOC)

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(CSV)

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2 Dec 2021

PONE-D-21-22519Health and economic burden of foodborne zoonotic diseases in Amhara region, EthiopiaPLOS ONE

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Academic Editor

PLOS ONE

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Additional Editor Comments (if provided):

This manuscript investigates health and economic burden of foodborne zoonotic diseases in Amhara region, Ethiopia. I commend the authors for conceptualizing this study, as the findings certainly add value to the literature. I have following comments:

1) The title of the manuscript should be framed as per STROBE guideline.

2) Psychometrics of the survey instruments should be provided.

3) Sample size calculations including power analysis should be provided

4) Authors said they used multiple logistic regression model. However, there is a lack of clarity on what basis the model was built. Whether they used a-priori hypothesis or any stepwise input of parameters. This information should be provided in data analysis section.

5) Table#5: please correct title of the table as per the data.

Reviewers' comments:

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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: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: Comments on the article reviewed

Material and methods:

• What is meant by projected population?

• Sample size and sampling method not properly documented. How 435 households were selected from 3 towns and method of recruitment of the respondents in the study is not clear.

• The term “haphazardly recruited” is not statistically correct.

• Animal source food consumption habits should be documented in either introduction or results or discussion.

• Grammatical errors are there in the text. It should be written in past tense but at some places, it is written in present or future tense.

• In data management and data analysis, write down the methods/software used e.g. Excel, SPSS etc.

Results

• Did not discuss the socio-demographic profile of the respondents in the starting of the results.

• Have not mentioned the risk factors or food consumption habits here.

Discussion

• Comparison with similar earlier studies is not sufficient.

Overall remarks

• The study findings are good in terms of health and economic burden. But need to rectify the material and methods. Also there is need to pay focus on risk factors and food consumption habits. Also give recommendations based on the findings of the study.

Reviewer #2: line 31- delet is and include 'may be'

line - 97- insert 'literature' after the word no

I had made corrections in the sticky notes and uploaded the pdf paper

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Reviewer #1: No

Reviewer #2: Yes: AMARENDRA MAHAPATRA

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Submitted filename: PONE-D-21-22519_reviewer.pdf

Click here for additional data file.

11 Dec 2021

We appreciate this thorough review and proper feedback. Indeed, we agree with this reviewer that there are several flaws and we have corrected according to the reviewers’ comments.

We checked the STROBE guidelines and mentioned the study design in the abstract.

We highlighted all changes in yellow in the original version of the manuscript and we responded to all specific comments below, indicating line numbers in the revised manuscript where changes were made.

Submitted filename: Response to Reviewers.doc

Click here for additional data file.

16 Dec 2021

Health and economic burden of foodborne zoonotic diseases in Amhara region, Ethiopia

PONE-D-21-22519R1

Dear Dr. Mekonnen,

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.

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Kind regards,

Bijaya Kumar Padhi, PhD, MPH

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

20 Dec 2021

PONE-D-21-22519R1

Health and economic burden of foodborne zoonotic diseases in Amhara region, Ethiopia

Dear Dr. Mekonnen:

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.

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

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Bijaya Kumar Padhi

Academic Editor

PLOS ONE