A Fuzzy-Based Approach for Cholera Risk Assessment and Vaccine Allocation

Common interventions to control the spread of cholera include improving sanitation, hygiene, and access safe drinking water providing epidemic regions with sufficient treatment kits oral vaccines. Due resources limitation, these should be guided by a risk assessment cholera-affected regions, thereby targeting based on their level. Cholera is very challenging because lack precise reliable data. This study proposes an approach for vaccine allocation, which consists two phases: (i) assessment, where fuzzy inference system (FIS) proposed evaluate level five indicators: (1) attack rate, (2) case fatality (3) number internally displaced persons, (4) accessibility water, sanitation (5) treatment; (ii) mixed-integer programming model used optimize allocation limited doses among multiple over periods while considering level, population efficacy. The answers questions where, what amounts, when send vaccines during 2-year horizon. Implementation illustrated using from Yemen, currently experiencing world’s worst outbreak according World Health Organization. results reveal usefulness in mapping risk, turn as effective guidance vaccine.