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      Validation of microbial source tracking markers for the attribution of fecal contamination in indoor-household environments of the Peruvian Amazon

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          Abstract

          The performance of eight microbial source tracking (MST) markers was evaluated in a low-resource, tropical community located in Iquitos, Peru. Fecal samples from humans, dogs, cats, rats, goats, buffalos, guinea-pigs, chickens, ducks, pigeons, and parrots were collected ( n = 117). All samples were tested with human ( BacHum, HF183-Taqman), dog ( BactCan), pig ( Pig-2-Bac), and avian ( LA35, Av4143, ND5, cytB) markers using quantitative PCR (qPCR). Internal validity metrics were calculated using all animal fecal samples, as well as animal fecal samples contextually relevant for the Peruvian Amazon. Overall, Pig-2-Bac performed best, with 100% sensitivity and 88.5% specificity to detect the correct fecal source. Human-associated markers showed a sensitivity of 80.0% and 76.7%, and specificity of 66.2% and 67.6%. When limiting the analysis to contextually relevant animal fecal samples for the Peruvian Amazon, Av143 surpassed cytB with 95.7% sensitivity and 81.8% specificity. BactCan demonstrated 100% sensitivity and 47.4% specificity. The gene copy number detected by BacHum and HF183-Taqman were positively correlated (Pearson's correlation coefficient: 0.785), as well as avian markers cytB with Av4143 (Pearson's correlation coefficient: 0.508) and nd5 (Pearson's correlation coefficient: 0.949). These findings suggest that markers such as Av4143, Pig2Bac, cytb and BacHum have acceptable performance to be impactful in source attribution studies for zoonotic enteric disease transmission in this and similar low-resource communities.

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          Highlights

          • First report of six fecal microbial source tracking markers and two avian mitochondrial microbial source tracking markers in the Peruvian Amazon.

          • Pig-2-Bac was the best performing marker, with 100% sensitivity and 88.5% specificity.

          • Based on the sensitivity and specificity, it is possible to use Av413, cytb and HF183-Taqman markers for the attribution of fecal contamination and exposure in this setting.

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          Most cited references43

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          Estimates of global, regional, and national morbidity, mortality, and aetiologies of diarrhoeal diseases: a systematic analysis for the Global Burden of Disease Study 2015

          Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) provides an up-to-date analysis of the burden of diarrhoeal diseases. This study assesses cases, deaths, and aetiologies spanning the past 25 years and informs the changing picture of diarrhoeal disease worldwide. Methods We estimated diarrhoeal mortality by age, sex, geography, and year using the Cause of Death Ensemble Model (CODEm), a modelling platform shared across most causes of death in the GBD 2015 study. We modelled diarrhoeal morbidity, including incidence and prevalence, using a meta-regression platform called DisMod-MR. We estimated aetiologies for diarrhoeal diseases using a counterfactual approach that incorporates the aetiology-specific risk of diarrhoeal disease and the prevalence of the aetiology in diarrhoea episodes. We used the Socio-demographic Index, a summary indicator derived from measures of income per capita, educational attainment, and fertility, to assess trends in diarrhoeal mortality. The two leading risk factors for diarrhoea—childhood malnutrition and unsafe water, sanitation, and hygiene—were used in a decomposition analysis to establish the relative contribution of changes in diarrhoea disability-adjusted life-years (DALYs). Findings Globally, in 2015, we estimate that diarrhoea was a leading cause of death among all ages (1·31 million deaths, 95% uncertainty interval [95% UI] 1·23 million to 1·39 million), as well as a leading cause of DALYs because of its disproportionate impact on young children (71·59 million DALYs, 66·44 million to 77·21 million). Diarrhoea was a common cause of death among children under 5 years old (499 000 deaths, 95% UI 447 000–558 000). The number of deaths due to diarrhoea decreased by an estimated 20·8% (95% UI 15·4–26·1) from 2005 to 2015. Rotavirus was the leading cause of diarrhoea deaths (199 000, 95% UI 165 000–241 000), followed by Shigella spp (164 300, 85 000–278 700) and Salmonella spp (90 300, 95% UI 34 100–183 100). Among children under 5 years old, the three aetiologies responsible for the most deaths were rotavirus, Cryptosporidium spp, and Shigella spp. Improvements in safe water and sanitation have decreased diarrhoeal DALYs by 13·4%, and reductions in childhood undernutrition have decreased diarrhoeal DALYs by 10·0% between 2005 and 2015. Interpretation At the global level, deaths due to diarrhoeal diseases have decreased substantially in the past 25 years, although progress has been faster in some countries than others. Diarrhoea remains a largely preventable disease and cause of death, and continued efforts to improve access to safe water, sanitation, and childhood nutrition will be important in reducing the global burden of diarrhoea. Funding Bill & Melinda Gates Foundation.
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            Pathogen-specific burdens of community diarrhoea in developing countries: a multisite birth cohort study (MAL-ED).

            Most studies of the causes of diarrhoea in low-income and middle-income countries have looked at severe disease in people presenting for care, and there are few estimates of pathogen-specific diarrhoea burdens in the community.
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              Effects of water quality, sanitation, handwashing, and nutritional interventions on diarrhoea and child growth in rural Kenya: a cluster-randomised controlled trial

              Summary Background Poor nutrition and exposure to faecal contamination are associated with diarrhoea and growth faltering, both of which have long-term consequences for child health. We aimed to assess whether water, sanitation, handwashing, and nutrition interventions reduced diarrhoea or growth faltering. Methods The WASH Benefits cluster-randomised trial enrolled pregnant women from villages in rural Kenya and evaluated outcomes at 1 year and 2 years of follow-up. Geographically-adjacent clusters were block-randomised to active control (household visits to measure mid-upper-arm circumference), passive control (data collection only), or compound-level interventions including household visits to promote target behaviours: drinking chlorinated water (water); safe sanitation consisting of disposing faeces in an improved latrine (sanitation); handwashing with soap (handwashing); combined water, sanitation, and handwashing; counselling on appropriate maternal, infant, and young child feeding plus small-quantity lipid-based nutrient supplements from 6–24 months (nutrition); and combined water, sanitation, handwashing, and nutrition. Primary outcomes were caregiver-reported diarrhoea in the past 7 days and length-for-age Z score at year 2 in index children born to the enrolled pregnant women. Masking was not possible for data collection, but analyses were masked. Analysis was by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT01704105. Findings Between Nov 27, 2012, and May 21, 2014, 8246 women in 702 clusters were enrolled and randomly assigned an intervention or control group. 1919 women were assigned to the active control group; 938 to passive control; 904 to water; 892 to sanitation; 917 to handwashing; 912 to combined water, sanitation, and handwashing; 843 to nutrition; and 921 to combined water, sanitation, handwashing, and nutrition. Data on diarrhoea at year 1 or year 2 were available for 6494 children and data on length-for-age Z score in year 2 were available for 6583 children (86% of living children were measured at year 2). Adherence indicators for sanitation, handwashing, and nutrition were more than 70% at year 1, handwashing fell to less than 25% at year 2, and for water was less than 45% at year 1 and less than 25% at year 2; combined groups were comparable to single groups. None of the interventions reduced diarrhoea prevalence compared with the active control. Compared with active control (length-for-age Z score −1·54) children in nutrition and combined water, sanitation, handwashing, and nutrition were taller by year 2 (mean difference 0·13 [95% CI 0·01–0·25] in the nutrition group; 0·16 [0·05–0·27] in the combined water, sanitation, handwashing, and nutrition group). The individual water, sanitation, and handwashing groups, and combined water, sanitation, and handwashing group had no effect on linear growth. Interpretation Behaviour change messaging combined with technologically simple interventions such as water treatment, household sanitation upgrades from unimproved to improved latrines, and handwashing stations did not reduce childhood diarrhoea or improve growth, even when adherence was at least as high as has been achieved by other programmes. Counselling and supplementation in the nutrition group and combined water, sanitation, handwashing, and nutrition interventions led to small growth benefits, but there was no advantage to integrating water, sanitation, and handwashing with nutrition. The interventions might have been more efficacious with higher adherence or in an environment with lower baseline sanitation coverage, especially in this context of high diarrhoea prevalence. Funding Bill & Melinda Gates Foundation, United States Agency for International Development.
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                Author and article information

                Contributors
                Journal
                Sci Total Environ
                Sci. Total Environ
                The Science of the Total Environment
                Elsevier
                0048-9697
                1879-1026
                15 November 2020
                15 November 2020
                : 743
                : 140531
                Affiliations
                [a ]Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
                [b ]Faculty of Veterinary Medicine, Universidad Peruana Cayetano Heredia, San Martin de Porres, Lima, Peru
                [c ]Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
                [d ]Division of Infectious Diseases, University of Virginia, Charlottesville, VA, USA
                [e ]Asociacion Benefica Prisma, Iquitos, Peru
                [f ]Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
                [g ]Department of Molecular and Comparative Pathobiology, Johns Hopkins Bloomberg School of Medicine, Baltimore, MD, USA
                Author notes
                [* ]Corresponding author at: University of Virginia, Division of Infectious Diseases, International Health, Public Health Sciences, 345 Crispell Dr, Rm 2525, Charlottesville, VA, USA. mkosek@ 123456virginia.edu
                Article
                S0048-9697(20)34053-5 140531
                10.1016/j.scitotenv.2020.140531
                7511695
                32758812
                8afdb879-b8f2-4eb2-9f1b-ac2ef12863aa
                © 2020 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 5 May 2020
                : 23 June 2020
                : 24 June 2020
                Categories
                Article

                General environmental science
                microbial source tracking,qpcr,feces,validation
                General environmental science
                microbial source tracking, qpcr, feces, validation

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