RESUMEN
BACKGROUND: Electronic Disease Early Warning System (eDEWS) is one of the effective programs in epidemiological surveillance. OBJECTIVE: This study aimed to identify the strengths and weaknesses of eDEWS in Sana'a governorate, determine its usefulness, and assess its performance in terms of the system attributes, including simplicity, flexibility, data quality, acceptability, representativeness, timeliness, and stability. METHODS: Updated guidelines on the evaluation of public health surveillance from the Center for Disease Control and Prevention (CDC) were used to evaluate the eDEWS in Sana'a governorate. Stakeholders from different levels were interviewed about the performance of the eDEWS. RESULTS: The overall score for the usefulness of the eDEWS was good (mean=83%). The overall system performance was good (86%). The highest attribute score was 100% for representativeness and the lowest score was 70% for stability. The system simplicity and acceptability were good. Although the system representativeness and flexibility were excellent, the stability was average. System completeness and timeliness were 100%. CONCLUSIONS: In conclusion, eDEWS in Yemen is useful and met its main objective. The overall level of system performance was good.
RESUMEN
BACKGROUND: In war-torn Yemen, reports of confirmed cholera started in late September, 2016. The disease continues to plague Yemen today in what has become the largest documented cholera epidemic of modern times. We aimed to describe the key epidemiological features of this epidemic, including the drivers of cholera transmission during the outbreak. METHODS: The Yemen Health Authorities set up a national cholera surveillance system to collect information on suspected cholera cases presenting at health facilities. Individual variables included symptom onset date, age, severity of dehydration, and rapid diagnostic test result. Suspected cholera cases were confirmed by culture, and a subset of samples had additional phenotypic and genotypic analysis. We first conducted descriptive analyses at national and governorate levels. We divided the epidemic into three time periods: the first wave (Sept 28, 2016, to April 23, 2017), the increasing phase of the second wave (April 24, 2017, to July 2, 2017), and the decreasing phase of the second wave (July 3, 2017, to March 12, 2018). We reconstructed the changes in cholera transmission over time by estimating the instantaneous reproduction number, Rt. Finally, we estimated the association between rainfall and the daily cholera incidence during the increasing phase of the second epidemic wave by fitting a spatiotemporal regression model. FINDINGS: From Sept 28, 2016, to March 12, 2018, 1â103â683 suspected cholera cases (attack rate 3·69%) and 2385 deaths (case fatality risk 0·22%) were reported countrywide. The epidemic consisted of two distinct waves with a surge in transmission in May, 2017, corresponding to a median Rt of more than 2 in 13 of 23 governorates. Microbiological analyses suggested that the same Vibrio cholerae O1 Ogawa strain circulated in both waves. We found a positive, non-linear, association between weekly rainfall and suspected cholera incidence in the following 10 days; the relative risk of cholera after a weekly rainfall of 25 mm was 1·42 (95% CI 1·31-1·55) compared with a week without rain. INTERPRETATION: Our analysis suggests that the small first cholera epidemic wave seeded cholera across Yemen during the dry season. When the rains returned in April, 2017, they triggered widespread cholera transmission that led to the large second wave. These results suggest that cholera could resurge during the ongoing 2018 rainy season if transmission remains active. Therefore, health authorities and partners should immediately enhance current control efforts to mitigate the risk of a new cholera epidemic wave in Yemen. FUNDING: Health Authorities of Yemen, WHO, and Médecins Sans Frontières.
