Temporal dynamics, climate associations, and surveillance performance of Lassa fever in Nigeria, 2020-2025: a national longitudinal analysis.

BACKGROUND

We examined national temporal trends, laboratory-confirmation performance, and climate associations in Lassa fever surveillance in Nigeria from 2020 to 2025, and assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on surveillance metrics.

METHODS

We analyzed 307 consecutive weeks of national Lassa fever surveillance data using an ecological study design. Primary outcomes included confirmed-case counts, case fatality rate (CFR), and laboratory-confirmation rate (LCR). Temporal trends were evaluated using regression models, climate associations using correlation and negative binomial regression analyses, and the impact of COVID-19 using interrupted time-series analysis.

RESULTS

Overall, 47,029 suspected cases, 6,288 confirmed cases, and 975 deaths were reported. The mean LCR was 11.2% (standard deviation, 7.2%), declining from 18.4% in 2020 to 9.9% in 2025 (p <0.001). The overall CFR was 15.5%, with no significant downward trend over time. Confirmed cases were inversely associated with weekly rainfall (rs=-0.589, p <0.0001) and positively associated with mean temperature (rs=0.462, p<0.0001). Peak season incidence was 5.3-fold higher than that during off-peak periods. The COVID-19 lockdown period was associated with an immediate reduction in confirmed cases without a corresponding reduction in suspected cases.

CONCLUSION

Lassa fever surveillance in Nigeria from 2020 to 2025 was characterized by a declining LCR, persistently elevated CFR, and a climate-linked seasonal pattern of increasing intensity, findings that are consistent with, but do not definitively establish, systemic underascertainment. CFR trends may partly reflect case-mix variation and detection bias. Because of the ecological study design, causal inferences cannot be drawn. These findings underscore the need for resilient, climate-informed, One Health surveillance systems.