Background As of July 17, 2020, the COVID-19 pandemic has affected over 14 million people worldwide, with over 3.68 million cases in the United States. As the number of COVID-19 cases increased in Massachusetts, the Massachusetts Department of Public Health mandated that all health care workers be screened for symptoms daily prior to entering any hospital or health care facility. We rapidly created a digital COVID-19 symptom screening tool to enable this screening for a large, academic, integrated health care delivery system, Partners HealthCare, in Boston, Massachusetts. Objective The aim of this study is to describe the design and development of the COVID Pass COVID-19 symptom screening application and report aggregate usage data from the first three months of its use across the organization. Methods Using agile principles, we designed, tested, and implemented a solution over the span of one week using progressively customized development approaches as the requirements and use case become more solidified. We developed the minimum viable product (MVP) of a mobile-responsive, web-based, self-service application using research electronic data capture (REDCap). For employees without access to a computer or mobile device to use the self-service application, we established a manual process where in-person, socially distanced screeners asked employees entering the site if they have symptoms and then manually recorded the responses in an Office 365 Form. A custom .NET Framework application solution was developed as COVID Pass was scaled. We collected log data from the .NET application, REDCap, and Microsoft Office 365 from the first three months of enterprise deployment (March 30 to June 30, 2020). Aggregate descriptive statistics, including overall employee attestations by day and site, employee attestations by application method (COVID Pass automatic screening vs manual screening), employee attestations by time of day, and percentage of employees reporting COVID-19 symptoms, were obtained. Results We rapidly created the MVP and gradually deployed it across the hospitals in our organization. By the end of the first week, the screening application was being used by over 25,000 employees each weekday. After three months, 2,169,406 attestations were recorded with COVID Pass. Over this period, 1865/160,159 employees (1.2%) reported positive symptoms. 1,976,379 of the 2,169,406 attestations (91.1%) were generated from the self-service screening application. The remainder were generated either from manual attestation processes (174,865/2,169,406, 8.1%) or COVID Pass kiosks (25,133/2,169,406, 1.2%). Hospital staff continued to work 24 hours per day, with staff attestations peaking around shift changes between 7 and 8 AM, 2 and 3 PM, 4 and 6 PM, and 11 PM and midnight. Conclusions Using rapid, agile development, we quickly created and deployed a dedicated employee attestation application that gained widespread adoption and use within our health system. Further, we identified 1865 symptomatic employees who otherwise may have come to work, potentially putting others at risk. We share the story of our implementation, lessons learned, and source code (via GitHub) for other institutions who may want to implement similar solutions.

The authors examine mothers and decision making during childhood febrile illness in rural Nigeria in this article. Employing a cross-sectional descriptive community survey, we elicited information from four categories of caregivers with the help of structured questionnaires. Apart from sociostructural economic factors, the authors reveal how interlocking objectives and values as expressed in extended family institutions functioned to influence both behavior and decision making of mothers. We suggest expanding the target of health education in the rural areas to include the family as an extended structure.

BackgroundThe COVID-19 pandemic has impacted over 1 million people across the globe, with over 330,000 cases in the United States. To help limit the spread in Massachusetts, the Department of Public Health required that all healthcare workers must be screened for symptoms daily -individuals with symptoms may not work. We rapidly created a digital COVID-19 symptom screening tool for a large, academic, integrated healthcare delivery system, Partners HealthCare, in Boston, Massachusetts.

IntroductionWestern Area (WA) of Sierra Leone including the capital, Freetown, experienced an unprecedented outbreak of Ebola from 2014 to 2015. At the onset of the epidemic, there was little information about the epidemiology, transmission dynamics, and risk factors in urban settings as previous outbreaks were limited to rural/semi-rural settings. This study, therefore, aimed to describe the epidemiology of the outbreak and the factors which had most impact on the transmission of the epidemic and whether there were different drivers from those previously described in rural settings.MethodsWe conducted a descriptive epidemiology study in WA, Sierra Leone using secondary data from the National Ebola outbreak database. We also reviewed the Ebola situation reports, response strategy documents, and other useful documents.ResultsA total of 4,955 Ebola cases were identified between June 2014 and November 2015, although there were reports of cases occurring in WA toward end of May. All wards were affected, and Waterloo Area I (Ward 330), the capital city of Western Area Rural District, recorded the highest numbers of cases (580) and deaths (236). Majority of cases (63.4%) and deaths (66.8%) were in WA Urban District (WAU); 44 cases were imported from other provinces. Only 20% of cases had a history of contact with an Ebola case, and more than 30% were death alerts. Equal numbers of males and females were infected, and very few cases (3.2%) were health workers. Overall, transmission was through contact with infected individuals, and intense transmission occurred at the community level. In WAU, transmission was mostly between neighbors and among inhabitants of shared accommodations. The drivers of transmission included high population movement to and from WA, overcrowding, fear and lack of trust in the response, and negative community behaviors. Transmission was mostly through contact and with limited transmission through sex and breast milk.ConclusionThe unprecedented outbreak in WA was attributed to delayed detection, inadequate preparedness and response, intense population movements, overcrowding, and unresponsive communities. Anticipation, strengthening preparedness for early detection, and swift and effective response remains critical in mitigating a potential urban explosion of similar future outbreaks.

Introduction: many studies have shown that unimproved water sources, inadequate sanitation facilities and poor hygiene are the main causes of diarrheal diseases, especially in developing countries. The aim of this study was to determine the prevalence and risk factors associated with diarrheal diseases in Sierra Leone. Methods: a cross-sectional study was conducted in March 2019. We used a questionnaire to collect data from study participants. Descriptive statistical analysis was followed to determine frequencies and percentages. Univariate analysis was used to find any association between dependent variable and independent variables. Independent variables that had an association in univariate were included in the multivariate model. Results: we surveyed 1,002 households (516 in rural and 486 in urban), and 2,311 respondents in four districts. The main source of income was farming 437 (43.6%). A total of 49 (54.2%) households earned below the national minimum wage per month. Females represented 61.9% of respondents. A total of 242 (32.2%) households had one to five household members and 229 (30.5%) households had more than ten members. Around 88.9% of households in urban, and 42.2% rural areas use improved water sources. The prevalence of diarrheal diseases was 12.3%. Multivariate analysis showed that using of unimproved water sources (aOR=1.9; 95% CI, 1.01 to 3.63, p=0.045), and large family size (aOR= 2.5; 95% CI, 1.18 to 5.35, p=0.017) were associated with diarrheal disease. Conclusion: we concluded that the risk factors associated with diarrheal diseases included unimproved water sources and large family size. More efforts required to improve water resources, adequate sanitation, and hygiene, particularly in rural areas.