Estimating time-varying transmission and oral cholera vaccine effectiveness in Haiti and Cameroon, 2021-2023
medrxiv(2024)
Abstract
In 2023, cholera affected approximately 1 million people and caused more than 5000 deaths globally, predominantly in low-income and conflict settings. In recent years, the number of new cholera outbreaks has grown rapidly. Further, ongoing cholera outbreaks have been exacerbated by conflict, climate change, and poor infrastructure, resulting in prolonged crises. As a result, the demand for treatment and intervention is quickly outpacing existing resource availability. Prior to improved water and sanitation systems, cholera — a disease primarily transmitted via contaminated water sources — also routinely ravaged high-income countries. Crumbling infrastructure and climate change are now putting new locations at risk — even in high-income countries. Thus, understanding the transmission and prevention of cholera is critical. Combating cholera requires multiple interventions, the most common being behavioral education and water treatment. Two-dose oral cholera vaccination (OCV) is often used as a complement to these interventions. Due to limited supply, countries have recently switched to single-dose vaccines (OCV1). One challenge lies in understanding where to allocate OCV1 in a timely manner, especially in settings lacking well-resourced public health surveillance systems. As cholera occurs primarily in low-income and conflict settings, timely, accurate, and openly accessible outbreak data are typically inaccessible for disease modeling and subsequent decision-making. In this study, we demonstrated the value of open-access data to rapidly estimate disease transmission and vaccine effectiveness. Specifically, we obtained non-machine readable (NMR) epidemic curves for recent cholera outbreaks in two countries, Haiti and Cameroon, from figures published in situation and disease outbreak news reports. We used computational digitization techniques to derive weekly counts of cholera cases. Given these data, we leveraged EpiEstim — an open-source modeling platform — to derive rapid estimates of time-varying disease transmission via the effective reproduction number (Rt). We used VaxEstim, a recent extension of this platform allowing the estimation of vaccine effectiveness via the relation between the basic reproductive number (R), Rt, and vaccine coverage, to compare OCV1 effectiveness in the two considered countries. Here, with Haiti and Cameroon as case studies, we demonstrated the first implementation of VaxEstim in low-resource settings. In the initial phase of the outbreak, weekly rolling average estimates of Rt were elevated in both countries: 2.60 in Haiti [95% credible interval: 2.42-2.79] and 1.90 in Cameroon [1.14-2.95]. Similarly, in both countries, this period of high transmission preceded a longer period during which Rt oscillated around the critical threshold of 1. VaxEstim results suggest that Haiti had higher OCV1 effectiveness than Cameroon (75.32% effective [54.00-86.39%] vs. 56.21% [18.87-84.94%]). This work underscores the value of combining NMR sources of outbreak case data with computational techniques and the utility of VaxEstim for rapid, inexpensive estimation of vaccine effectiveness in data-poor outbreak settings.
### Competing Interest Statement
ENH reports contracts from the Global Listening Project and Council on Foreign Relations outside of the submitted work. All other authors declare no competing interests.
### Funding Statement
This research was supported in part by the National Institute of General Medical Sciences, MIT-Harvard Broad Institute Eric & Wendy Schmidt Center, National Institutes of Health (R35GM146974) and the National Science Foundation (SES2200228 & IIS2229881). The funding sources had no involvement in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.
### Author Declarations
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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
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All data in this analysis are openly available and provided via citations.
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