Background: Cholera outbreaks are influenced by climatic, demographic, and socioeconomic factors. This study examines how these elements interact over time and across regions in Mozambique to inform more effective and timely interventions. Understanding these dynamics is crucial for controlling outbreaks.

Methods: Researchers used monthly provincial cholera case data (2000–2018) from Mozambique’s Ministry of Health. These were linked to Socioeconomic indicators (from Demographic and Health Surveys), Climatic variables such as  relative humidity (RH), mean temperature, and precipitation, and Normalized Difference Vegetation Index (NDVI). A Bayesian spatial-temporal model was developed, assuming a negative binomial distribution for cholera cases. The analysis used Integrated Nested Laplace Approximation (INLA) and Distributed Lag Nonlinear Models (DLNM) to capture delayed effects of climate factors, adjusted for social variables.

Results: A total of 153,941 cholera cases were reported from 2000-2018. The peak incidence occurred in 2002, 181.5 per 100 000 population. Mean temperatures above 24°C increased cholera risk compared to 23°C. At a mean temperature of 19°C, risk increased at a 5–6 month lag. Between 19°C and 22°C, risk was lower at 0–4 month lags. Precipitation of 223.3 mm, with a 1-month lag, increased risk by 57% (RR 1.57, 95% CI: 1.06–2.31). At a 3-month lag, NDVI of 0.137 increased cholera risk by 22% (RR 1.220, 95% CI: 1.042–1.430) compared to NDVI 0.2. Higher relative humidity (RH = 54%) was associated with 62% increased risk at a 4-month lag (RR 1.620, 95% CI: 1.124–2.342). Owning a radio (used for health messaging) significantly reduced cholera risk (RR 0.628, 95% CI: 0.476–0.821). Sharing toilet facilities significantly increased cholera risk (RR 1.365, 95% CI: 1.060–1.765).

Conclusions: This study quantified how climate and socioeconomic conditions influence cholera incidence across space and time in Mozambique. The identified lag effects of climatic variables (temperature, rainfall, humidity, vegetation) can help establish early warning systems and inform targeted, climate-adaptive interventions for cholera prevention and control.

Keywords: Cholera; Mozambique; DLNM; Climate variability