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Background In 2023, cholera caused over 95 000 deaths globally, predominantly in low-income and conflict settings, and contributed to the wasting, stunting and malnutrition of millions in countries where the disease is endemic. Moreover, the frequency and magnitude of cholera outbreaks are rising. As a result, the demand for outbreak control interventions is quickly outpacing existing resources. Oral cholera vaccination (OCV) is one intervention among many used to limit further transmission. Since 2022, one-dose OCV (OCV1) has replaced the standard two-dose OCV due to limited global supply. However, only a handful of on-the-ground surveys of OCV1 effectiveness presently exist. Objective This study aims to assess the transmission of cholera in outbreak settings using digital public health approaches and quantify OCV1 effectiveness in complement to on-the-ground surveys. Methods Using Haiti and Cameroon as natural case studies representing two disparate geographical and sociodemographic contexts, we employed computational digitisation techniques to extract weekly case counts from non–machine-readable images of outbreak epidemic curves. We then leveraged the R package EpiEstim to derive estimates of the effective reproduction number ( R t ). To assess OCV1 effectiveness in the two considered countries, we applied VaxEstim , an extension of EpiEstim requiring three inputs: the basic reproduction number ( R 0 ), R t, and vaccine coverage. Notably, our work provides the first known real-world application of VaxEstim in low-resource settings. Results Early in either outbreak, weekly estimates of R t were elevated (Haiti, 2.60 (95% credible interval (CrI) 2.42 to 2.79); Cameroon, 1.90 (95% CrI 1.14 to 2.95)). Thereafter, R t estimates oscillated around the critical threshold of 1 in both settings. Haiti exhibited marginally higher OCV1 effectiveness than Cameroon (75.3% (95% CrI 54.0 to 86.4%) versus 54.9% (95% CrI 18.9 to 84.9%)). Conclusions This study underscores the value of combining digitised case data with computational techniques and the utility of VaxEstim for rapid, inexpensive estimation of vaccine effectiveness in data-poor outbreak settings.
Hulland et al. (Fri,) studied this question.