by
Richard K Mugambe;
Jane S Mselle;
Tony Ssekamatte;
Moses Ntanda;
John B Isunju;
Solomon T Wafula;
Winnifred K Kansiime;
Prossy Isubikalu;
David Ssemwanga;
Habib Yakubu;
Christine Moe
Background: Hand hygiene (HH) among healthcare workers (HCWs) is critical for infection prevention and control (IPC) in healthcare facilities (HCFs). Nonetheless, it remains a challenge in HCFs, largely due to lack of high-impact and efficacious interventions. Environmental cues and mobile phone health messaging (mhealth) have the potential to improve HH compliance among HCWs, however, these remain under-studied. Our study will determine the impact of mhealth hygiene messages and environmental cues on HH practice among HCWs in the Greater Kampala Metropolitan Area (GKMA). Methods: The study is a cluster-randomized trial, which will be guided by the behaviour centred design model and theory for behaviour change. During the formative phase, we shall conduct 30 key informants’ interviews and 30 semi-structured interviews to explore the barriers and facilitators to HCWs’ HH practice. Besides, observations of HH facilities in 100 HCFs will be conducted. Findings from the formative phase will guide the intervention design during a stakeholders’ insight workshop. The intervention will be implemented for a period of 4 months in 30 HCFs, with a sample of 450 HCWs who work in maternity and children’s wards. HCFs in the control arm will receive innovatively designed HH facilities and supplies. HCWs in the intervention arm, in addition to the HH facilities and supplies, will receive environmental cues and mhealth messages. The main outcome will be the proportion of utilized HH opportunities out of the 9000 HH opportunities to be observed. The secondary outcome will be E. coli concentration levels in 100mls of hand rinsates from HCWs, an indicator of recent fecal contamination and HH failure. We shall run multivariable logistic regression under the generalized estimating equations (GEE) framework to account for the dependence of HH on the intervention. Discussion: The study will provide critical findings on barriers and facilitators to HH practice among HCWs, and the impact of environmental cues and mhealth messages on HCWs’ HH practice. Trial registration: ISRCTN Registry with number ISRCTN98148144. The trial was registered on 23/11/2020.
Enteric fever is a severe systemic infection caused by Salmonella enterica serovar Typhi (ST) and Salmonella enterica serovar Paratyphi A (SPA). Detection of ST and SPA in wastewater can be used as a surveillance strategy to determine burden of infection and identify priority areas for water, sanitation, and hygiene interventions and vaccination campaigns. However, sensitive and specific detection of ST and SPA in environmental samples has been challenging. In this study, we developed and validated two methods for concentrating and detecting ST/SPA from wastewater: the Moore swab trap method for qualitative results, and ultrafiltration (UF) for sensitive quantitative detection, coupled with qPCR. We then applied these methods for ST and SPA wastewater surveillance in Kolkata, India and Dhaka, Bangladesh, two enteric fever endemic areas. The qPCR assays had a limit of detection of 17 equivalent genome copies (EGC) for ST and 25 EGC for SPA with good reproducibility. In seeded trials, the Moore swab method had a limit of detection of approximately 0.05–0.005 cfu/mL for both ST and SPA. In 53 Moore swab samples collected from three Kolkata pumping stations between September 2019 and March 2020, ST was detected in 69.8% and SPA was detected in 20.8%. Analysis of sewage samples seeded with known amount of ST and SPA and concentrated via the UF method, followed by polyethylene glycol precipitation and qPCR detection demonstrated that UF can effectively recover approximately 8, 5, and 3 log10 cfu of seeded ST and SPA in 5, 10, and 20 L of wastewater. Using the UF method in Dhaka, ST was detected in 26.7% (8/30) of 20 L drain samples with a range of 0.11–2.10 log10 EGC per 100 mL and 100% (4/4) of 20 L canal samples with a range of 1.02–2.02 log10 EGC per 100 mL. These results indicate that the Moore swab and UF methods provide sensitive presence/absence and quantitative detection of ST/SPA in wastewater samples.
Background: WHO and UNICEF have proposed an action plan to achieve universal water, sanitation and hygiene (WASH) coverage in healthcare facilities (HCFs) by 2030. The WASH targets and indicators for HCFs include: an improved water source on the premises accessible to all users, basic sanitation facilities, a hand washing facility with soap and water at all sanitation facilities and patient care areas. To establish viable targets for WASH in HCFs, investigation beyond 'access' is needed to address the state of WASH infrastructure and service provision. Patient and caregiver use of WASH services is largely unaddressed in previous studies despite being critical for infection control. Methods: The state of WASH services used by staff, patients and caregivers was assessed in 17 rural HCFs in Rwanda. Site selection was non-random and predicated upon piped water and power supply. Direct observation and semi-structured interviews assessed drinking water treatment, presence and condition of sanitation facilities, provision of soap and water, and WASH-related maintenance and record keeping. Samples were collected from water sources and treated drinking water containers and analyzed for total coliforms, E. coli, and chlorine residual. Results: Drinking water treatment was reported at 15 of 17 sites. Three of 18 drinking water samples collected met the WHO guideline for free chlorine residual of > 0.2 mg/l, 6 of 16 drinking water samples analyzed for total coliforms met the WHO guideline of < 1 coliform/100 mL and 15 of 16 drinking water samples analyzed for E. coli met the WHO guideline of < 1 E. coli/100 mL. HCF staff reported treating up to 20 L of drinking water per day. At all sites, 60% of water access points (160 of 267) were observed to be functional, 32% of hand washing locations (46 of 142) had water and soap and 44% of sanitary facilities (48 of 109) were in hygienic condition and accessible to patients. Regular maintenance of WASH infrastructure consisted of cleaning; no HCF had on-site capacity for performing repairs. Quarterly evaluations of HCFs for Rwanda's Performance Based Financing system included WASH indicators. Conclusions: All HCFs met national policies for water access, but WHO guidelines for environmental standards including water quality were not fully satisfied. Access to WASH services at the HCFs differed between staff and patients and caregivers.
Environmental surveillance can be used for monitoring enteric disease in a population by detecting pathogens, shed by infected people, in sewage. Detection of pathogens depends on many factors: infection rates and shedding in the population, pathogen fate in the sewerage network, and also sampling sites, sample size, and assay sensitivity. This complexity makes the design of sampling strategies challenging, which creates a need for mathematical modeling to guide decision making. In the present study, a model was developed to simulate pathogen shedding, pathogen transport and fate in the sewerage network, sewage sampling, and detection of the pathogen. The simulation study used Salmonella enterica serovar Typhi (S. Typhi) as the target pathogen and two wards in Kolkata, India as the study area.
Five different sampling strategies were evaluated for their sensitivity of detecting S. Typhi, by sampling unit: sewage pumping station, shared toilet, adjacent multiple shared toilets (primary sampling unit), pumping station + shared toilets, pumping station + primary sampling units. Sampling strategies were studied in eight scenarios with different geographic clustering of risk, pathogen loss (decay, leakage), and sensitivity of detection assays. A novel adaptive sampling site allocation method was designed, that updates the locations of sampling sites based on their performance. We then demonstrated how the simulation model can be used to predict the performance of environmental surveillance and how it is improved by optimizing the allocation of sampling sites.
The results are summarized as a decision tree to guide the sampling strategy based on disease incidence, geographic distribution of risk, pathogen loss, and the sensitivity of the detection assay. The adaptive sampling site allocation method consistently outperformed alternatives with fixed site locations in most scenarios. In some cases, the optimum allocation method increased the median sensitivity from 45% to 90% within 20 updates.
Inadequate sanitation can lead to exposure to fecal contamination through multiple environmental pathways and can result in adverse health outcomes. By understanding the relative importance of multiple exposure pathways, sanitation interventions can be tailored to those pathways with greatest potential public health impact. The SaniPath Exposure Assessment Tool allows users to identify and quantify human exposure to fecal contamination in low-resource urban settings through a systematic yet customizable process. The Tool includes: a project management platform; mobile data collection and a data repository; protocols for primary data collection; and automated exposure assessment analysis.
The data collection protocols detail the process of conducting behavioral surveys with households, school children, and community groups to quantify contact with fecal exposure pathways and of collecting and analyzing environmental samples for E. coli as an indicator of fecal contamination. Bayesian analyses are used to estimate the percentage of the population exposed and the mean dose of fecal exposure from microbiological and behavioral data. Fecal exposure from nine pathways (drinking water, bathing water, surface water, ocean water, open drains, floodwater, raw produce, street food, and public or shared toilets) can be compared through a common metric-estimated ingestion of E. coli units (MPN or CFU) per month. The Tool generates data visualizations and recommendations for interventions designed for both scientific and lay audiences.
When piloted in Accra, Ghana, the results of the Tool were comparable with that of an in-depth study conducted in the same neighborhoods and highlighted consumption of raw produce as a dominant exposure pathway. The Tool has been deployed in nine cities to date, and the results are being used by local authorities to design and prioritize programming and policy. The SaniPath Tool is a novel approach to support public-health evidence-based decision-making for urban sanitation policies and investments.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Rapid urbanization has led to a growing sanitation crisis in urban areas of Bangladesh and potential exposure to fecal contamination in the urban environment due to inadequate sanitation and poor fecal sludge management. Limited data are available on environmental fecal contamination associated with different exposure pathways in urban Dhaka. We conducted a cross-sectional study to explore the magnitude of fecal contamination in the environment in low-income, high-income, and transient/floating neighborhoods in urban Dhaka. Ten samples were collected from each of 10 environmental compartments in 10 different neighborhoods (4 low-income, 4 high-income and 2 transient/floating neighborhoods). These 1,000 samples were analyzed with the IDEXX-Quanti-Tray technique to determine most-probable-number (MPN) of E. coli. Samples of open drains (6.91 log10 MPN/100 mL), surface water (5.28 log10 MPN/100 mL), floodwater (4.60 log10 MPN/100 mL), produce (3.19 log10 MPN/serving), soil (2.29 log10 MPN/gram), and street food (1.79 log10 MPN/gram) had the highest mean log10 E. coli contamination compared to other samples. The contamination concentrations did not differ between low-income and high-income neighborhoods for shared latrine swabs, open drains, municipal water, produce, and street foodsamples. E. coli contamination levels were significantly higher (p <0.05) in low-income neighborhoods compared to high-income for soil (0.91 log10 MPN/gram, 95% CI, 0.39, 1.43), bathing water (0.98 log10 MPN/100 mL, 95% CI, 0.41, 1.54), non-municipal water (0.64 log10 MPN/100 mL, 95% CI, 0.24, 1.04), surface water (1.92 log10 MPN/100 mL, 95% CI, 1.44, 2.40), and floodwater (0.48 log10 MPN/100 mL, 95% CI, 0.03, 0.92) samples. E. coli contamination were significantly higher (p<0.05) in low-income neighborhoods compared to transient/floating neighborhoods for drain water, bathing water, non-municipal water and surface water. Future studies should examine behavior that brings people into contact with the environment and assess the extent of exposure to fecal contamination in the environment through multiple pathways and associated risks.
by
Yuke Wang;
Wolfgang Mairinger;
Suraja J. Raj;
Habib Yakubu;
Casey Siesel;
Jamie Green;
Sarah Durry;
George Joseph;
Mahbubur Rahman;
Nuhu Amin;
Md. Zahidul Hassan;
James Wicken;
Dany Dourng;
Eugene Larbi;
Lady Asantewa B. Adomako;
Ato Kwamena Senayah;
Benjamin Doe;
Richard Buamah;
Joshua Nii Noye Tetteh-Nortey;
Gagandeep Kang;
Arun Karthikeyan;
Sheela Roy;
Joe Brown;
Bacelar Muneme;
Seydina O. Sene;
Benedict Tuffuor;
Richard K. Mugambe;
Najib Lukooya Bateganya;
Trevor Surridge;
Grace Mwanza Ndashe;
Kunda Ndashe;
Radu Ban;
Alyse Schrecongost;
Christine Moe
Background
During 2014 to 2019, the SaniPath Exposure Assessment Tool, a standardized set of methods to evaluate risk of exposure to fecal contamination in the urban environment through multiple exposure pathways, was deployed in 45 neighborhoods in ten cities, including Accra and Kumasi, Ghana; Vellore, India; Maputo, Mozambique; Siem Reap, Cambodia; Atlanta, United States; Dhaka, Bangladesh; Lusaka, Zambia; Kampala, Uganda; Dakar, Senegal.
Objective
Assess and compare risk of exposure to fecal contamination via multiple pathways in ten cities.
Methods
In total, 4053 environmental samples, 4586 household surveys, 128 community surveys, and 124 school surveys were collected. E. coli concentrations were measured in environmental samples as an indicator of fecal contamination magnitude. Bayesian methods were used to estimate the distributions of fecal contamination concentration and contact frequency. Exposure to fecal contamination was estimated by the Monte Carlo method. The contamination levels of ten environmental compartments, frequency of contact with those compartments for adults and children, and estimated exposure to fecal contamination through any of the surveyed environmental pathways were compared across cities and neighborhoods.
Results
Distribution of fecal contamination in the environment and human contact behavior varied by city. Universally, food pathways were the most common dominant route of exposure to fecal contamination across cities in low-income and lower-middle-income countries. Risks of fecal exposure via water pathways, such as open drains, flood water, and municipal drinking water, were site-specific and often limited to smaller geographic areas (i.e., neighborhoods) instead of larger areas (i.e., cities).
Conclusions
Knowledge of the relative contribution to fecal exposure from multiple pathways, and the environmental contamination level and frequency of contact for those “dominant pathways” could provide guidance for Water, Sanitation, and Hygiene (WASH) programming and investments and enable local governments and municipalities to improve intervention strategies to reduce the risk of exposure to fecal contamination.
Introduction: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA monitoring in wastewater has become an important tool for Coronavirus Disease 2019 (COVID-19) surveillance. Grab (quantitative) and passive samples (qualitative) are two distinct wastewater sampling methods. Although many viral concentration methods such as the usage of membrane filtration and skim milk are reported, these methods generally require large volumes of wastewater, expensive lab equipment, and laborious processes. Methods: The objectives of this study were to compare two workflows (Nanotrap® Microbiome A Particles coupled with MagMax kit and membrane filtration workflows coupled with RNeasy kit) for SARS-CoV-2 recovery in grab samples and two workflows (Nanotrap® Microbiome A Particles and skim milk workflows coupled with MagMax kit) for SARS-CoV-2 recovery in Moore swab samples. The Nanotrap particle workflow was initially evaluated with and without the addition of the enhancement reagent 1 (ER1) in 10 mL wastewater. RT-qPCR targeting the nucleocapsid protein was used for detecting SARS-CoV-2 RNA. Results: Adding ER1 to wastewater prior to viral concentration significantly improved viral concentration results (P < 0.0001) in 10 mL grab and swab samples processed by automated or manual Nanotrap workflows. SARS-CoV-2 concentrations in 10 mL grab and Moore swab samples with ER1 processed by the automated workflow as a whole showed significantly higher (P < 0.001) results than 150 mL grab samples using the membrane filtration workflow and 250 mL swab samples using the skim milk workflow, respectively. Spiking known genome copies (GC) of inactivated SARS-CoV-2 into 10 mL wastewater indicated that the limit of detection of the automated Nanotrap workflow was ~11.5 GC/mL using the RT-qPCR and 115 GC/mL using the digital PCR methods. Discussion: These results suggest that Nanotrap workflows could substitute the traditional membrane filtration and skim milk workflows for viral concentration without compromising the assay sensitivity. The manual workflow can be used in resource-limited areas, and the automated workflow is appropriate for large-scale COVID-19 wastewater-based surveillance.
Noroviruses are known to bind to histo-blood group antigens (HBGAs) and the specific binding patterns depend on the virus genotype. However, the development of point-of-care diagnostic assays based on this binding has been challenging due to low assay sensitivity. This study utilized a well-defined stool collection from a GII.2 Snow Mountain Virus (SMV) human challenge study to investigate virus recovery from stool and emesis samples using HBGA-coated beads. SMV was recovered from H type III-coated beads for 13 stool specimens out of 27 SMV-positive specimens tested. After adjusting for non-specific binding to PEG-coated beads, the mean percent recovery by H type III-coated beads was 308.11% +/− 861.61.
Recovery by H type III ligands was subject-specific and weakly correlated with stool consistency. Input virus titer was not correlated with SMV recovery. The results suggest that the generally low virus recovery we observed may be due to bead saturation or hindrance by existing glycans in the matrix that precluded the virus from being captured by the synthetic glycans. These results indicate a strong role for subject-specific and matrix effects in HBGA binding by SMV. Further investigation of the nature of this interference is needed to facilitate development of high sensitivity diagnostic assays.
Background: Globally, in 2010, approximately 1.5 billion people were infected with at least one species of soil-transmitted helminth (STH), Ascaris lumbricoides, Trichuris trichiura, hookworm (Ancylostoma duodenale and Necator americanus). Infection occurs through ingestion or contact (hookworm) with eggs or larvae in the environment from fecal contamination. To control these infections, the World Health Organization recommends periodic mass treatment of at-risk populations with deworming drugs. Prevention of these infections typically relies on improved excreta containment and disposal. Most evidence of the relationship between sanitation and STH has focused on household-level access or usage, rather than community-level sanitation usage. We examined the association between the proportion of households in a community with latrines in use and prevalence of STH infections among school-aged children.
Methods: Data on STH prevalence and household latrine usage were obtained during four population-based, cross-sectional surveys conducted between 2011 and 2014 in Amhara, Ethiopia. Multilevel regression was used to estimate the association between the proportion of households in the community with latrines in use and presence of STH infection, indicated by > 0 eggs in stool samples from children 6–15 years old.
Results: Prevalence of STH infection was estimated as 22% (95% CI: 20–24%), 14% (95% CI: 13–16%), and 4% (95% CI: 4–5%) for hookworm, A. lumbricoides, and T. trichiura, respectively. Adjusting for individual, household, and community characteristics, hookworm prevalence was not associated with community sanitation usage. Trichuris trichuria prevalence was higher in communities with sanitation usage ≥ 60% versus sanitation usage < 20%. Association of community sanitation usage with A. lumbricoides prevalence depended on household sanitation. Community sanitation usage was not associated with A. lumbricoides prevalence among households with latrines in use. Among households without latrines in use, A. lumbricoides prevalence was higher comparing communities with sanitation usage ≥ 60% versus < 20%. Households with a latrine in use had lower prevalence of A. lumbricoides compared to households without latrines in use only in communities where sanitation usage was ≥ 80%.
Conclusions: We found no evidence of a protective association between community sanitation usage and STH infection. The relationship between STH infection and community sanitation usage may be complex and requires further study.