Molecular Identification of Malaria Vector in Gusau Township, Nigeria is a research paper published in International Journal of Science for Global Sustainability (2023). On theSindex it has a DataRank of 0.104. It has been cited 1 time.
There about 460 Anopheles species recognized, over 100 can transmit human malaria but only 30–40 commonly transmit parasites of the genus Plasmodium, which cause malaria. Anopheles gambiae is the principal vector of the most dangerous malaria parasite species in Africa, which is Plasmodium falciparum. Anopheles gambiae are a complex consisting of eight morphologically indistinguishable species and each of the members of the complex having unique biology, ecology and behaviour and should be studied and differentiated. The research objective was to identify the species of malaria vector in Gusau township Nigeria using molecular biological technique to know the exact malaria vector. Knowledge of the exact malaria vector in a given environment enables formulating a carefully designed tailor-made vector control measure. Indoor and outdoor mosquito samples were collected from selected areas in five wards of Gusau township using standard collection methods, for a period of twelve months. The samples were identified using polymerase chain reaction (PCR) technique and the result showed Anopheles gambiae in all sites of sample collection. It is therefore recommended that integrated malaria vector control should be adopted in the mosquito control programme because Anopheles gambiae is rugged and can be difficult to control and/or eradicate because of the emerging insecticide resistance and its close association with human host.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.104
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.