Key Characteristics and Perception of Different Outbreak Surveillance Systems in Côte d'Ivoire: Cross-Sectional Survey Among Users.

Background: Accurate and timely infectious disease surveillance is pivotal for effective public health responses. An important component of this is the disease surveillance tools used. Understanding views and experiences of users is crucial for informing policy decisions and ensuring the seamless functioning of surveillance systems. Objective: In this study, we aimed to assess the user perceptions of 3 disease surveillance tools used in Côte d'Ivoire, namely, MAGPI, District Health Information Software 2 (DHIS2), and Surveillance Outbreak Response Management and Analysis System (SORMAS), the latter was implemented in 2021 within a pilot scheme. Methods: We conducted interviews and a web-based survey distributed to users of the 3 surveillance tools. The survey assessed users' views of the surveillance tools' usefulness, ease of use, feelings toward the tool, conditions that may influence the use, and other characteristics. The descriptive analysis compared responses from SORMAS, MAGPI, and DHIS2 users, providing a comprehensive evaluation of their experiences. Results: Among the 159 respondents who actively use one of the systems, MAGPI was the most widely used surveillance tool among respondents (n=127, 79.9%), followed by DHIS2 (n=108, 67.9%), and SORMAS (n=25, 15.7%). In terms of users' perceptions, SORMAS, despite its limited implementation, emerged as a tool that allows for data analysis and had the most comprehensive set of functionalities. DHIS2 was appreciated for its frequency of report provision, although users reported occasional IT system failures. MAGPI was recognized for its ease of use but was reported to lack certain functionalities offered by the other surveillance systems. Conclusions: This study offers valuable insights into the perceptions of disease surveillance tools users in Côte d'Ivoire. While all systems were positively regarded, each exhibited strengths and weaknesses addressing different needs and functionalities. Policy makers and health officials can use these findings to enhance existing tools or consider a unified approach for infectious disease surveillance systems. Understanding users' perspectives allows them to optimize the choice of surveillance tools, ultimately strengthening public health responses in Côte d'Ivoire and potentially serving as a model for other countries facing similar decisions in their health care systems.

Characteristics of Hospitalized COVID-19 Patients at Admission and Factors Associated with Clinical Severity in Low- and Middle-Income Countries: An Observational Study.

Despite the numerous articles published on the clinical characteristics and outcomes of COVID-19 with regard to high-income countries, little is known about patients in low- and middle-income countries (LMIC) in this context. The objective of this observational, prospective, hospital-based multicentric study was to describe clinical features and outcomes of laboratory-confirmed COVID-19 patients hospitalized in each of the participating centers in Bangladesh, Guinea, Ivory Coast, Lebanon, Madagascar, and Mali during the first year of the pandemic (March 5, 2020 to May 4, 2021). The study outcome was the clinical severity of COVID-19, defined as hospitalization in intensive care unit or death. Multivariate logistic regression models were performed to identify independent variables associated with disease severity. Overall, 1,096 patients were included. The median age was 49.0 years, ranging from 38.0 in Mali to 63.0 years in Guinea. The overall clinical severity of COVID-19 was 12.3%, ranging from 6.4% in Mali to 18.8% in Guinea. In both groups of patients <60 and ≥60 years old, cardiovascular diseases (adjusted odds ratio [aOR]: 1.99; 95% CI: 1.13-3.50, P = 0.02; aOR: 2.47; 95% CI: 1.33-4.57, P = 0.004) were independently associated with clinical severity, whereas in patients <60 years, diabetes (aOR: 2.13; 95% CI: 1.11-4.10, P = 0.02) was also associated with clinical severity. Our findings suggest that COVID-19-related severity and death in LMICs are mainly driven by older age. However, the presence of chronic diseases can also increase the risk of severity especially in younger patients.