Scientific Reports (Aug 2023)

Spatial distribution and ecological niche modeling of geographical spread of Anopheles gambiae complex in Nigeria using real time data

  • Adedapo Adeogun,
  • Ayodele Samuel Babalola,
  • Okefu Oyale Okoko,
  • Tolulope Oyeniyi,
  • Ahmed Omotayo,
  • Romoke Tawakalitu Izekor,
  • Oluwakemi Adetunji,
  • Abiodun Olakiigbe,
  • Olalekan Olagundoye,
  • Monsuru Adeleke,
  • Cynthia Ojianwuna,
  • Dagona Adamu,
  • Abdullahi Daskum,
  • Jibrin Musa,
  • Obadiah Sambo,
  • Oduola Adedayo,
  • Petrus Uchenna Inyama,
  • Lazarus Samdi,
  • Abiodun Obembe,
  • Musa Dogara,
  • Poloma Kennedy,
  • Suleiman Mohammed,
  • Rebecca Samuel,
  • Chioma Amajoh,
  • Musa Adesola,
  • Mohammed Bala,
  • Mary Esema,
  • Mamudu Omo-Eboh,
  • Marianne Sinka,
  • Olufunmilayo Ajoke Idowu,
  • Adeolu Ande,
  • Israel Olayemi,
  • Abdulsalami Yayo,
  • Perpetua Uhomoibhi,
  • Samson Awolola,
  • Babatunde Salako

DOI
https://doi.org/10.1038/s41598-023-40929-5
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 18

Abstract

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Abstract The need for evidence-based data, to inform policy decisions on malaria vector control interventions in Nigeria, necessitated the establishment of mosquito surveillance sites in a few States in Nigeria. In order to make evidence-based-decisions, predictive studies using available data becomes imperative. We therefore predict the distribution of the major members of the Anopheles gambiae s.l. in Nigeria. Immature stages of Anopheles were collected from 72 study locations which span throughout the year 2020 resulted in the identification of over 60,000 Anopheline mosquitoes. Of these, 716 breeding sites were identified with the presence of one or more vector species from the An. gambiae complex and were subsequently used for modelling the potential geographical distribution of these important malaria vectors. Maximum Entropy (MaxEnt) distribution modeling was used to predict their potentially suitable vector habitats across Nigeria. A total of 23 environmental variables (19 bioclimatic and four topographic) were used in the model resulting in maps of the potential geographical distribution of three dominant vector species under current climatic conditions. Members of the An. gambiae complex dominated the collections (98%) with Anopheles stephensi, Anopheles coustani, Anopheles funestus, Anopheles moucheti, Anopheles nilli also present. An almost equal distribution of the two efficient vectors of malaria, An. gambiae and Anopheles coluzzii, were observed across the 12 states included in the survey. Anopheles gambiae and Anopheles coluzzii had almost equal, well distributed habitat suitability patterns with the latter having a slight range expansion. However, the central part of Nigeria (Abuja) and some highly elevated areas (Jos) in the savannah appear not suitable for the proliferation of these species. The most suitable habitat for Anopheles arabiensis was mainly in the South-west and North-east. The results of this study provide a baseline allowing decision makers to monitor the distribution of these species and establish a management plan for future national mosquito surveillance and control programs in Nigeria.