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Background <p>Lassa fever is a recurrent public health threat in Nigeria, particularly in endemic regions such as Kogi State. Its transmission is closely tied to environmental and seasonal dynamics, especially those influencing rodent populations. Understanding these climatic influences is essential for strengthening disease surveillance and implementing timely interventions.</p> Methods <p>A descriptive cross-sectional study was conducted using retrospective epidemiological and climatic data from 2019 to 2024. Confirmed Lassa fever case records and meteorological variables (temperature, rainfall, and humidity) were analyzed using statistical correlation, regression models, and geospatial mapping.</p> Results <p>A consistent seasonal trend was observed, with the majority of cases occurring during the dry season (November–March), peaking in January 2022 and February 2024. Temperature showed a statistically significant positive correlation with Lassa fever incidence (<i>r</i> = 0.282, <i>p</i> = 0.029). Rainfall and humidity displayed weak or non-significant associations, though brief case surges followed isolated rainfall spikes in dry months. Spatial analysis identified Lokoja, Ibaji, and Dekina LGAs as hotspots, likely due to population density, food storage practices, and improved reporting. The regression model yielded modest explanatory power (R² = 0.089), but thresholds such as temperature &gt; 35&#xa0;°C and humidity between 60 and 80% emerged as potential early warning indicators.</p> Conclusion <p>Seasonal variation, particularly elevated temperatures during the dry season, plays a significant role in Lassa fever incidence in Kogi State. Integrating climatic, ecological, and epidemiological data into a real-time risk alert system under a One Health framework could enhance preparedness and response in high-risk areas.</p> Clinical trials number <p>Not applicable.</p>

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Impact of seasonal changes on the epidemiology of Lassa fever in a state in North Central, Nigeria

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月13日

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  • Onuche Noah John,
  • Adamu Ishaku Akyala,
  • Grace Itodo Eleojo,
  • Stephen Olaide Aremu,
  • Adams Okur Matthew,
  • Oli Peggy Elam,
  • Arinze Joseph Ezeobi,
  • Ojotule Augustine,
  • Segun Barnabas,
  • Umameh Augustine,
  • Oluwatoyin Joy Ayo,
  • Khadijat Mohammed,
  • Arome John Ameh,
  • Michael Sule Ohize,
  • Omale Shuaibu Thankgod,
  • Abdillahi Abdi Barkhadle

摘要

Background

Lassa fever is a recurrent public health threat in Nigeria, particularly in endemic regions such as Kogi State. Its transmission is closely tied to environmental and seasonal dynamics, especially those influencing rodent populations. Understanding these climatic influences is essential for strengthening disease surveillance and implementing timely interventions.

Methods

A descriptive cross-sectional study was conducted using retrospective epidemiological and climatic data from 2019 to 2024. Confirmed Lassa fever case records and meteorological variables (temperature, rainfall, and humidity) were analyzed using statistical correlation, regression models, and geospatial mapping.

Results

A consistent seasonal trend was observed, with the majority of cases occurring during the dry season (November–March), peaking in January 2022 and February 2024. Temperature showed a statistically significant positive correlation with Lassa fever incidence (r = 0.282, p = 0.029). Rainfall and humidity displayed weak or non-significant associations, though brief case surges followed isolated rainfall spikes in dry months. Spatial analysis identified Lokoja, Ibaji, and Dekina LGAs as hotspots, likely due to population density, food storage practices, and improved reporting. The regression model yielded modest explanatory power (R² = 0.089), but thresholds such as temperature > 35 °C and humidity between 60 and 80% emerged as potential early warning indicators.

Conclusion

Seasonal variation, particularly elevated temperatures during the dry season, plays a significant role in Lassa fever incidence in Kogi State. Integrating climatic, ecological, and epidemiological data into a real-time risk alert system under a One Health framework could enhance preparedness and response in high-risk areas.

Clinical trials number

Not applicable.