Critical failings in humanitarian response: a cholera outbreak in Kumer Refugee Camp, Ethiopia, 2023
Background
Every year, 60% of deaths from diarrhoeal disease occur in low and middle-income countries due to inadequate water, sanitation, and hygiene. In these countries, diarrhoeal diseases are the second leading cause of death in children under five, excluding neonatal deaths. The approximately 100,000 people residing in the Bentiu Internally Displaced Population (IDP) camp in South Sudan have previously experienced water, sanitation, and hygiene outbreaks, including an ongoing Hepatitis E outbreak in 2021. This study aimed to assess the gaps in Water, Sanitation, and Hygiene (WASH), prioritise areas for intervention, and advocate for the improvement of WASH services based on the findings.
Methods
A cross-sectional lot quality assurance sampling (LQAS) survey was conducted in ninety-five households to collect data on water, sanitation, and hygiene (WASH) coverage performance across five sectors. Nineteen households were allocated to each sector, referred to as supervision areas in LQAS surveys. Probability proportional to size sampling was used to determine the number of households to sample in each sector block selected using a geographic positioning system. One adult respondent, familiar with the household, was chosen to answer WASH-related questions, and one child under the age of five was selected through a lottery method to assess the prevalence of WASH-related disease morbidities in the previous two weeks. The data were collected using the KoBoCollect mobile application. Data analysis was conducted using R statistical software and a generic LQAS Excel analyser. Crude values, weighted averages, and 95% confidence intervals were calculated for each indicator. Target coverage benchmarks set by program managers and WASH guidelines were used to classify the performance of each indicator.
Results
The LQAS survey revealed that five out of 13 clean water supply indicators, eight out of 10 hygiene and sanitation indicators, and two out of four health indicators did not meet the target coverage. Regarding the clean water supply indicators, 68.9% (95% CI 60.8%-77.1%) of households reported having water available six days a week, while 37% (95% CI 27%-46%) had water containers in adequate condition. For the hygiene and sanitation indicators, 17.9% (95% CI 10.9%-24.8%) of households had handwashing points in their living area, 66.8% (95% CI 49%-84.6%) had their own jug for cleansing after defaecation, and 26.4% (95% CI 17.4%-35.3%) of households had one piece of soap. More than 40% of households wash dead bodies at funerals and wash their hands in a shared bowl. Households with sanitary facilities at an acceptable level were 22.8% (95% CI 15.6%-30.1%), while 13.2% (95% CI 6.6%-19.9%) of households had functioning handwashing points at the latrines. Over the previous two weeks, 57.9% (95% CI 49.6–69.7%) of households reported no diarrhoea, and 71.3% (95% CI 62.1%-80.6%) reported no eye infections among children under five.
Conclusion
The camp’s hygiene and sanitation situation necessitated immediate intervention to halt the hepatitis E outbreak and prevent further WASH-related outbreaks and health issues. The LQAS findings were employed to advocate for interventions addressing the WASH gaps, resulting in WASH and health actors stepping in.
This study evaluated an early warning, alert and response system for a crisis-affected population in Doolo zone, Somali Region, Ethiopia, in 2019–2021, with a history of epidemics of outbreak-prone diseases. To adequately cover an area populated by a semi-nomadic pastoralist, or livestock herding, population with sparse access to healthcare facilities, the surveillance system included four components: health facility indicator-based surveillance, community indicator- and event-based surveillance, and alerts from other actors in the area. This evaluation described the usefulness, acceptability, completeness, timeliness, positive predictive value, and representativeness of these components.
METHODS
We carried out a mixed-methods study retrospectively analysing data from the surveillance system February 2019–January 2021 along with key informant interviews with system implementers, and focus group discussions with local communities. Transcripts were analyzed using a mixed deductive and inductive approach. Surveillance quality indicators assessed included completeness, timeliness, and positive predictive value, among others.
RESULTS
1010 signals were analysed; these resulted in 168 verified events, 58 alerts, and 29 responses. Most of the alerts (46/58) and responses (22/29) were initiated through the community event-based branch of the surveillance system. In comparison, one alert and one response was initiated via the community indicator-based branch. Positive predictive value of signals received was about 6%. About 80% of signals were verified within 24 h of reports, and 40% were risk assessed within 48 h. System responses included new mobile clinic sites, measles vaccination catch-ups, and water and sanitation-related interventions. Focus group discussions emphasized that responses generated were an expected return by participant communities for their role in data collection and reporting. Participant communities found the system acceptable when it led to the responses they expected. Some event types, such as those around animal health, led to the community’s response expectations not being met.
CONCLUSIONS
Event-based surveillance can produce useful data for localized public health action for pastoralist populations. Improvements could include greater community involvement in the system design and potentially incorporating One Health approaches.
The Somali Region is one of the least developed regions of Ethiopia, with low coverage of healthcare services and recurrent disease outbreaks, floods, and malnutrition emergencies. MSF has been providing medical assistance in the Doolo Zone, Somali Region, since 2007. Following multiple disease outbreaks in 2017, MSF shifted focus to work primarily on early outbreak detection and provision of a timely response. In 2019, MSF established a “Tea Team surveillance team”; this combines health facility data with that from community indicator- and event-based surveillance systems. Data are collected from 32 locations (17 surveillance only and 15 non-permanent mobile clinic sites), as well as alerts from other actors in Doolo Zone. We aimed to evaluate the usefulness of the data generated by these different components.
METHODS
We used a mixed methods approach. Description of the surveillance system, quantitative analysis of retrospective data between February 2019 and January 2021, and focus group discussions were the main methods used to evaluate usefulness, acceptability, and other surveillance attributes. Quantitative analyses were done using R software (R Core Team, 2014) while qualitative data analysis was performed with NVivo software (QSR International Pty Ltd, Australia).
ETHICS
Permission to conduct the study was obtained from the Somali Regional Health Bureau. This study was approved by the MSF Ethics Review Board.
RESULTS
Over 1200 signals were reported to the Tea Team surveillance system over the evaluation period, with the majority being reported via the community event-based surveillance (CEBS) component. There were a total of 31 responses conducted between February 2019 and January 2021. 22 (84.6%) originated from CEBS system signals, one (3.8%) was from the community indicator-based surveillance (CIBS) system, 2 (7.7%) were from health facility indicator-based surveillance (HFIBS), and 6 (23.1%) came from other event-based surveillance systems. Most responses were triggered by population movements, suspected measles, and suspected acute watery diarrhoea. No responses arose from acute jaundice syndrome signals. MSF staff found the “Tea Team surveillance system” to have higher acceptability in non-emergency situations, but indicated lower acceptability during a crisis, due to data processing times and rigidity of the HFIBS online database. The surveillance system has complex data management procedures leading to potential underreporting of signals and difficulties with routine data quality monitoring. Project staff considered the CEBS and CIBS components to be more flexible than HFIBS. The system was sufficiently flexible to integrate with Covid-19 surveillance.
CONCLUSION
The Tea Team surveillance system is a comprehensive and useful system to detect and respond to public health events in a pastoralist population. Simplification of the surveillance system and greater standardisation of the data management processes will increase the utility of the system.
CONFLICTS OF INTEREST
None declared