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Background <p>The dynamics of vector-borne disease transmission depend on the abundances of vectors. The dominant malaria vector species complex of <i>Anopheles gambiae</i> sensu lato is a target of vector control strategies designed to reduce and eliminate malaria transmission. The three most widely distributed dominant malaria vectors within the species complex are <i>An. arabiensis</i>, <i>An. coluzzii</i> and <i>An. gambiae</i> sensu stricto.</p> Methods <p>Previous studies across the extent of the species complex range have been restricted to annual predictions of species occurrence or relative abundance. This study incorporated relative abundance data at the species level and abundance data at the species complex level to estimate and predict daily equilibrium vector abundances of each species. Statistical models with interpretable parameters were used to gain insight into how factors such as meteorological conditions, insecticide-treated net use and human density affect the spatial and temporal predictions. The statistical models were used to predict daily equilibrium vector abundance, which is an important factor in indices of malaria transmission such as the basic reproduction number and vectorial capacity.</p> Results <p>Meteorological factors, such as precipitation and relative humidity, and human factors, such as population density and insecticide-treated nets, were important predictors of these three malaria vector species in Africa. Insecticide-treated&#xa0;net use was negatively associated with per capita vector abundance of the <i>An. gambiae</i> species complex and interacted with year to suggest a negative effect on the ratio of <i>An. gambiae</i> s.s. to <i>An. arabiensis</i> at the end of the prediction period that extended from 2002 to 2020. A predicted increasing interannual trend for <i>An. coluzzii</i> was potentially caused by changing species identification methods.</p> Conclusions <p>The predicted equilibrium abundances of the three species showed potentially high levels of geographical overlap, niche overlap and evidence for stable coexistence despite substantial interspecific competition. Improving collection of longitudinal species abundance data across the spatial range of the <i>An. gambiae</i> species complex will facilitate future explorations of causal hypotheses that relate vector abundance to control measures, malaria interventions and meteorological conditions.</p>

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Prediction of mosquito vector abundance for three species in the Anopheles gambiae complex

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月3日

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  • Geoffrey R. Hosack,
  • Maud El-Hachem,
  • Adrien Ickowicz,
  • Nicholas J. Beeton,
  • Andrew Wilkins,
  • Keith R. Hayes,
  • Samuel S. C. Rund,
  • Sarah A. Kelly,
  • Mary Ann McDowell

摘要

Background

The dynamics of vector-borne disease transmission depend on the abundances of vectors. The dominant malaria vector species complex of Anopheles gambiae sensu lato is a target of vector control strategies designed to reduce and eliminate malaria transmission. The three most widely distributed dominant malaria vectors within the species complex are An. arabiensis, An. coluzzii and An. gambiae sensu stricto.

Methods

Previous studies across the extent of the species complex range have been restricted to annual predictions of species occurrence or relative abundance. This study incorporated relative abundance data at the species level and abundance data at the species complex level to estimate and predict daily equilibrium vector abundances of each species. Statistical models with interpretable parameters were used to gain insight into how factors such as meteorological conditions, insecticide-treated net use and human density affect the spatial and temporal predictions. The statistical models were used to predict daily equilibrium vector abundance, which is an important factor in indices of malaria transmission such as the basic reproduction number and vectorial capacity.

Results

Meteorological factors, such as precipitation and relative humidity, and human factors, such as population density and insecticide-treated nets, were important predictors of these three malaria vector species in Africa. Insecticide-treated net use was negatively associated with per capita vector abundance of the An. gambiae species complex and interacted with year to suggest a negative effect on the ratio of An. gambiae s.s. to An. arabiensis at the end of the prediction period that extended from 2002 to 2020. A predicted increasing interannual trend for An. coluzzii was potentially caused by changing species identification methods.

Conclusions

The predicted equilibrium abundances of the three species showed potentially high levels of geographical overlap, niche overlap and evidence for stable coexistence despite substantial interspecific competition. Improving collection of longitudinal species abundance data across the spatial range of the An. gambiae species complex will facilitate future explorations of causal hypotheses that relate vector abundance to control measures, malaria interventions and meteorological conditions.