Transmission Sources of Waterborne Viruses in South Sudan Refugee Camps

Guerrero-Latorre, Laura; Hundesa, Ayalkibet; Gironés, Rosina

doi:10.1002/clen.201500358

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…Finally, no positive results were obtained from water samples using the PCR method. One possible reason was that the transmission and circulating period of the viruses may have occurred weeks ago when human cases were infected during the outbreak [38]. On the other hand, detection of water samples was conducted by the local CDC without equipment for water enrichment.…”

Section: Discussionmentioning

confidence: 99%

Epidemiological investigation of a tap water-mediated hepatitis E virus genotype 4 outbreak in Zhejiang Province, China

Chen

Cao²,

Xie

et al. 2016

Epidemiol. Infect.

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An outbreak of acute hepatitis recently occurred in a nursing home in Zhejiang Province, China. The objectives of this study were to confirm the outbreak and identify the aetiology, source and transmission patterns. All residents and staff in or near the nursing home during the period from 1 October 2014 to 21 May 2015 were investigated regarding hygiene and for epidemiological information including water and food (eating meat especially pork products). Serum and stool specimens were collected for detection of hepatitis E virus (HEV) antibodies using ELISA and RNA using RT-PCR. Samples that were RNA positive were genotyped. Of 185 senior residents and 24 staff in the nursing home, there were 37 laboratory-confirmed cases during the outbreak. Of these cases, 12 patients (three deaths) were symptomatic with jaundice, a common clinical symptom for hepatitis E infection. HEV strains were isolated from three cases and they formed a single cluster within genotype 4d. A case-control study was conducted to investigate potential risk factors for the outbreak and the results revealed that cases more often washed their dishes and rinsed their mouths using tap water than the controls (P < 0·05). Based on hygiene investigation and meteorological information, it is likely that HEV-infected sewage and faeces contaminated the water network on rainy days. Collectively, these results suggest that the outbreak of HEV genotype 4 infection was most likely caused by contaminated tap water rather than food.

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Section: Discussionmentioning

confidence: 99%

Epidemiological investigation of a tap water-mediated hepatitis E virus genotype 4 outbreak in Zhejiang Province, China

Chen

Cao²,

Xie

et al. 2016

Epidemiol. Infect.

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“…Less frequently reported risk factors were waste management (n=2, 2%) (Connolly et al, 2004;Prothero, 1994), limited access to health care (n=2, 2%) (Connolly et al, 2004;Kimbrough et al, 2012) and young age (n=2, 2%) (Desenclos et al, 1988;Mellou et al, 2017). Pregnancy (n=3, 3%) (Cronin et al, 2008;Guerrero-Latorre et al, 2016;Mcgready et al, 2010) and HIV-positive status (n=2, 2%) (Cronin et al, 2008;Kimbrough et al, 2012) were reported as morbidity and mortality risk factors.…”

Section: Exposures Outcomes and Risk Factorsmentioning

confidence: 99%

Environmental health conditions in the transitional stage of forcible displacement: A systematic scoping review

Cooper

Behnke

Cronk

et al. 2021

Science of The Total Environment

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“…In refugee and internally displaced persons (IDP) settlements, water-users typically do not have drinking water piped to their premises; instead, they collect water from public distribution points (tapstands) which they then transport, store, and use over time in their dwellings. Recontamination of previously safe drinking water during this post-distribution period of collection, transport, and storage is an important factor in waterborne illness outbreaks, having been linked to outbreaks of cholera, hepatitis E, and shigellosis in refugee and IDP settlements in Kenya, Malawi, Sudan, South Sudan, and Uganda [2][3][4][5][6][7][8][9]. To prevent outbreaks in refugee and IDP settlements, drinking water needs to be protected against pathogenic recontamination until the end of the household storage period when the final cup is consumed.…”

Section: Introductionmentioning

confidence: 99%

Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts?

et al. 2022

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Ensuring sufficient free residual chlorine (FRC) up to the time and place water is consumed in refugee settlements is essential for preventing the spread of waterborne illnesses. Water system operators need accurate forecasts of FRC during the household storage period. However, factors that drive FRC decay after water leaves the piped distribution system vary substantially, introducing significant uncertainty when modelling point-of-consumption FRC. Artificial neural network (ANN) ensemble forecasting systems (EFS) can account for this uncertainty by generating probabilistic forecasts of point-of-consumption FRC. ANNs are typically trained using symmetrical error metrics like mean squared error (MSE), but this leads to forecast underdispersion forecasts (the spread of the forecast is smaller than the spread of the observations). This study proposes to solve forecast underdispersion by training an ANN-EFS using cost functions that combine alternative metrics (Nash-Sutcliffe efficiency, Kling Gupta Efficiency, Index of Agreement) with cost-sensitive learning (inverse FRC weighting, class-based FRC weighting, inverse frequency weighting). The ANN-EFS trained with each cost function was evaluated using water quality data from refugee settlements in Bangladesh and Tanzania by comparing the percent capture, confidence interval reliability diagrams, rank histograms, and the continuous ranked probability. Training the ANN-EFS using the cost functions developed in this study produced up to a 70% improvement in forecast reliability and dispersion compared to the baseline cost function (MSE), with the best performance typically obtained by training the model using Kling-Gupta Efficiency and inverse frequency weighting. Our findings demonstrate that training the ANN-EFS using alternative metrics and cost-sensitive learning can improve the quality of forecasts of point-of-consumption FRC and better account for uncertainty in post-distribution chlorine decay. These techniques can enable humanitarian responders to ensure sufficient FRC more reliably at the point-of-consumption, thereby preventing the spread of waterborne illnesses.

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Transmission Sources of Waterborne Viruses in South Sudan Refugee Camps

Cited by 5 publications

References 24 publications

Epidemiological investigation of a tap water-mediated hepatitis E virus genotype 4 outbreak in Zhejiang Province, China

Epidemiological investigation of a tap water-mediated hepatitis E virus genotype 4 outbreak in Zhejiang Province, China

Environmental health conditions in the transitional stage of forcible displacement: A systematic scoping review

Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts?

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