LATEBREAKER
Infectious Disease
Estimating real-time reproductive number and oral cholera vaccine effectiveness for outbreaks in Haiti and Cameroon, 2021-2023 Erin Hulland Frame* Erin Hulland Frame Marie-Laure Charpignon Ghinwa El Hayek Lihong Zhao Angel N Desai Maimuna S Majumder
Cholera sickens millions of people a year globally, mostly in low-income and conflict settings. Prior to improved water and sanitation systems cholera also routinely ravaged higher income countries. With crumbling infrastructure and climate change putting new locations at increased risk, the threat of cholera persists. Thus, understanding its transmission and prevention are critical.
Responding to a cholera outbreak is multi-pronged, with behavioral education and water treatment being among the most-used interventions. Oral cholera vaccination (OCV) is often used in complement, with a recent switch to single-dose implementation (OCV1) due to limited supply. Therefore, understanding where to best allocate OCV1—and doing so in a timely manner—is essential, especially in such settings where detailed data are often scarce.
In this pursuit, we leveraged EpiEstim—an open source modeling platform— to provide rapid estimates of time-varying disease transmission via the effective reproductive number (RE). An extension of this platform (VaxEstim) allows identification of gaps in vaccine coverage. We use VaxEstim to compare two recent cholera outbreaks in Cameroon and Haiti using aggregated publicly-available data; estimate the effectiveness of OCV1 campaigns; and identify climate and sociodemographic factors related to context-specific cholera transmission.
We observe high initial 4-day rolling average estimates of RE in both Haiti and Cameroon, with Haiti having larger initial values (2.1 [95% CI:2.0-2.3] vs. 1.8 [1.1-2.7]); both high transmission periods were followed by a longer period oscillating around 1. We observe higher OCV1 effectiveness in Haiti than Cameroon (75.3% [54.0-86.4] vs. 56.2% [18.9-84.9]), and note differences in improved water access, population density, and climate variables, likely contributing to this variability. This work demonstrates the utility of VaxEstim for quick and inexpensive estimation of vaccine effectiveness in data-poor outbreak settings.
