TY  - JOUR
AU  - Valerio, Mariana Gasparoto Pereira
AU  - Laher, Beverly
AU  - Phuka, John
AU  - Lichand, Guilherme
AU  - Paolotti, Daniela
AU  - Leal Neto, Onicio
PY  - 2024
DA  - 2024/7/16
TI  - Participatory Disease Surveillance for the Early Detection of Cholera-Like Diarrheal Disease Outbreaks in Rural Villages in Malawi: Prospective Cohort Study
JO  - JMIR Public Health Surveill
SP  - e49539
VL  - 10
KW  - participatory surveillance
KW  - digital epidemiology
KW  - interactive voice response
KW  - cholera
KW  - public health
KW  - outbreak
KW  - cohort study
KW  - public health surveillance
KW  - health technology
KW  - digital surveillance
AB  - Background: Cholera-like diarrheal disease (CLDD) outbreaks are complex and influenced by environmental factors, socioeconomic conditions, and population dynamics, leading to limitations in traditional surveillance methods. In Malawi, cholera is considered an endemic disease. Its epidemiological profile is characterized by seasonal patterns, often coinciding with the rainy season when contamination of water sources is more likely. However, the outbreak that began in March 2022 has extended to the dry season, with deaths reported in all 29 districts. It is considered the worst outbreak in the past 10 years. Objective: This study aims to evaluate the feasibility and outcomes of participatory surveillance (PS) using interactive voice response (IVR) technology for the early detection of CLDD outbreaks in Malawi. Methods: This longitudinal cohort study followed 740 households in rural settings in Malawi for 24 weeks. The survey tool was designed to have 10 symptom questions collected every week. The proxies’ rationale was related to exanthematic, ictero-hemorragica for endemic diseases or events, diarrhea and respiratory/targeting acute diseases or events, and diarrhea and respiratory/targeting seasonal diseases or events. This work will focus only on the CLDD as a proxy for gastroenteritis and cholera. In this study, CLDD was defined as cases where reports indicated diarrhea combined with either fever or vomiting/nausea. Results: During the study period, our data comprised 16,280 observations, with an average weekly participation rate of 35%. Maganga TA had the highest average of completed calls, at 144.83 (SD 10.587), while Ndindi TA had an average of 123.66 (SD 13.176) completed calls. Our findings demonstrate that this method might be effective in identifying CLDD with a notable and consistent signal captured over time (R2=0.681404). Participation rates were slightly higher at the beginning of the study and decreased over time, thanks to the sensitization activities rolled out at the CBCCs level. In terms of the attack rates for CLDD, we observed similar rates between Maganga TA and Ndindi TA, at 16% and 15%, respectively. Conclusions: PS has proven to be valuable for the early detection of epidemics. IVR technology is a promising approach for disease surveillance in rural villages in Africa, where access to health care and traditional disease surveillance methods may be limited. This study highlights the feasibility and potential of IVR technology for the timely and comprehensive reporting of disease incidence, symptoms, and behaviors in resource-limited settings. 
SN  - 2369-2960
UR  - https://publichealth.jmir.org/2024/1/e49539
UR  - https://doi.org/10.2196/49539
UR  - http://www.ncbi.nlm.nih.gov/pubmed/39012690
DO  - 10.2196/49539
ID  - info:doi/10.2196/49539
ER  -