• Users Online: 7275
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2016  |  Volume : 3  |  Issue : 1  |  Page : 45-50

Malaria parasite species prevalence and transmission dynamics at selected sites in the Western highlands of Kenya

1 Department of Medical Microbiology, College of Health Sciences, Moi University, Eldoret, Kenya
2 Department of Clinical Medicine, College of Health Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
3 Department of Biological Sciences Masinde Muliro University of Science and Technology, Kakamega, Kenya

Date of Web Publication22-Dec-2015

Correspondence Address:
Mulambalah Chrispinus Siteti
Department of Medical Microbiology and Parasitology, College of Health Sciences, Moi University, Eldoret
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2348-3334.172399

Rights and Permissions

Background: Malaria in the Western Kenya highlands is unpredictable sometimes leading to epidemics that result in dramatic emergencies in terms of severe morbidity and mortality. This places enormous strain on health facilities disrupting fragile health care services culminating into crises. This underlies the need for a better understanding of the disease dynamics and determinants to formulate specific and focused intervention strategies. Aim: One year study was undertaken in Kipsamoite and Kapsisiywa in Nandi County to evaluate Plasmodium species prevalence and transmission risk in the general population and specific age groups. Subjects and Methods: Positive blood smears were used to determine monthly malaria prevalence, age-group prevalence. Malaria risk in population was worked out using adult to child ratio (ACR). Results: ACR results indicated a less immune population in which all age groups and sexes were equally susceptible to malaria. Plasmodium falciparum was most prevalent (90%, n = 264) while Plasmodium malariae (10%, n = 30). There was significant difference in the malaria parasite species prevalence (χ2,P < 0.05), but there was no significant difference in parasite species prevalence between the study sites (χ2, P > 0.05). Conclusions: Malaria transmission dynamics were similar in both sites, largely driven by seasonality, had an even age distribution implying that the threat of epidemics was real should all age-groups become exposed to parasites and conditions of disease transmission become favorable.

Keywords: Adult to child ratio, disease dynamics, epidemics, prevalence, transmission

How to cite this article:
Siteti MC, Injete SD, Wanyonyi WA. Malaria parasite species prevalence and transmission dynamics at selected sites in the Western highlands of Kenya. CHRISMED J Health Res 2016;3:45-50

How to cite this URL:
Siteti MC, Injete SD, Wanyonyi WA. Malaria parasite species prevalence and transmission dynamics at selected sites in the Western highlands of Kenya. CHRISMED J Health Res [serial online] 2016 [cited 2022 May 20];3:45-50. Available from: https://www.cjhr.org/text.asp?2016/3/1/45/172399

  Introduction Top

Malaria transmission dynamics is highly variable throughout Africa. Transmission can occur throughout the year or only during a couple of months, with heterogeneities observed between years within the same locale.[1] Levels of human malaria transmission may be described as high, moderate, low, seasonal, perennial, or characterized by periodic epidemics and outbreaks.

In the highland areas of Africa, malaria is a devastating disease with high mortality and morbidity demanding a rapid comprehensive response. In other settings, it can be a more pernicious public health threat than in others. In Kenya, nearly 7 million people translating into approximately 23% of the total population reside in 15 counties defined as highland malaria epidemic-prone areas.[2] Since the mid-20th century, epidemic malaria has been reported in the Western highlands of Kenya than any other part of the country.[3],[4],[5],[6],[7],[8] The frequency and intensity of outbreaks increased significantly in first decade of the 21st century.[9],[10] Even though there has not been any report of major outbreak in recent years, the forecast for the future is not favorable in this region. Malaria epidemics are most likely to be frequent and intense in future if the current intervention strategies and surveillance are not sustained, closely evaluated and monitored. Therefore, there is need for further search for more epidemiological determinants associated with general malaria transmission that could lead to evolution of epidemics in the Western highlands of Kenya.

The genesis of malaria epidemic in the Western highlands of Kenya is multi-factorial and may be related to the local vector species [11] climate and environmental changes [12],[13],[14] anti-malarial drug resistance [15] and decline in population immunity.[16] However, the contribution of each of these factors to any given epidemic is variable from year to year in different localities within the highlands. This is supported by the discovery of “malaria hot spots” within the Western highlands with unique epidemiological characteristics.[17] There is need to generate more information on possible factors that can lead to the genesis and propagation of malaria and epidemics in the highlands for appropriate malaria and epidemic control in future.

Most malaria epidemics in the Western highlands have been associated with a single Plasmodium species. There are reports that epidemics may occur by the superposition of any of the known malaria parasite species: Plasmodium falciparum, Plasmodium ovale, Plasmodium malariae, and Plasmodium vivax. The spread of such epidemics may involve several chains of transmission [18] such that a relatively large area may appear to show a single prolonged epidemic. These may actually be a number of overlapping local epidemics in different phases and associated with different malaria parasite species [19] and would require diverse intervention strategies. Whenever they occur, such epidemics present severe and serious public health problems in the highlands with disastrous consequences at individual, household, community, regional, and national level.[20]

In this regard, there is need for continuous assessment of the parasite species circulating in highland malaria epidemic-prone areas to have an idea on how fast or slow malaria transmission or epidemic can spread in the community. This together with early detection of community vulnerability and transmission risk indicators can be used to predict future epidemics, plan for a phased control response and allow organizations capacity to monitor and assess the situation before committing valuable resources.

The study seeks to determine the Plasmodium species, malaria prevalence and transmission stability at two malaria epidemic-prone study sites of Kipsamoite and in Nandi County. Previous studies indicated that malaria transmission occurs in “hot spots”[17] and is seasonal and sporadic in both sites.[21] Information on Plasmodium species prevalence and transmission dynamics at specific sites is limited in the Western highlands of Kenya. The study findings are likely to form basis for policy formulation on malaria prevention and control in the highlands of Kenya.

  Subjects and Methods Top

The study area and sites

The Kenya Western highlands are found at an altitude of 1500 m above sea level to the west of the Great Rift Valley including the following counties: Kisii, Kakamega, Kericho, Kakamega, Nandi, Trans-Nzoia and Bungoma. The study was conducted in Nandi County at two sites: Kipsamoite and Kapsisiywa selected because malaria epidemics and outbreaks had been reported within the sites previously and availability of two government run health centers where vast majority (>80%) sought medical care and therefore ideal sampling points.

Subject recruitment and ethical considerations

Ethical clearance was obtained from ethical committee at Kapsabet County hospital before the project started. The community at the study sites was sensitized to understand and appreciated the study objectives. Informed verbal or written consent was obtained from all those willing to participate or from their guardians before recruitment was undertaken. Included in the study were those who had been residents for a period of 6 months preceding study. Those excluded were nonresidents, pregnant women, those on anti-malarial treatment and those who declined to give informed consent.

Participants were recruited into the study between January and December 2014 by sampling carried out at 2 week intervals. Because the prevalence of malaria was not well known in the study area, a 50% estimate of the individuals attending the health centers was used for the patients who visited the health centers, which gave the best sample size used. Participant recruitment was based on individuals presenting with and without malaria symptoms at health centers. Participant sampling from the study population was by a consecutive series of participants attending clinic until sample size was or the nearest figure to sample size was obtained.

Identification of Plasmodium species and determination of malaria parasitemia

Consenting individuals had 0.5–1.0 ml of blood obtained by the following procedure at the health centers: Preparation of site (finger) with alcohol, pricking of the fingertip with a lancet and obtaining the blood sample on a clean 25 mm × 75 mm slide in a 10–30 s period. The blood was spread out to make thick and thin smears, dried and fixed in methanol and stained in 4% Giemsa at recommended pH of 7.2 for 30 min.

All stained blood films were examined microscopically at 1000 × objective under oil immersion to for malaria parasites. Microscopic examination was done at the health centers and the presence of malaria parasite species sexual or asexual stages in thick blood smears was considered a positive diagnosis. A second and third blood examination reading was done by different technicians to ensure quality assurance. Thin blood smears were used for Plasmodium species identification. The whole slide was carefully scanned before being declared negative. Slides were reported negative for parasites only after examining at least 50 oil-immersion fields of the thick smears. An individual was defined as a malaria “case” if her/his blood smear was positive for P. falciparum or any other Plasmodium species known to cause disease in man. All individuals diagnosed with clinical malaria or positive blood films at the health centers were given treatment by the clinic staff according to the Kenya Ministry of Health guidelines.

Determination of malaria age prevalence and transmission stability

The ratio of adults positive for malaria to children positive for malaria designated as adult to child ratio (ACR) was used to determine the transmission stability as described elsewhere.[7] The ages of the subjects were stratified into the following age groups in years: <1, 1–4, 5–9, 10–14, 15–19, and >19.[22] Age specific prevalence was determined by expressing positive blood smears as a percentage of all examined smears (for the age group). The Chi-square test (χ2) was used to determine the differences in prevalence among the age groups. Malaria transmission stability was determined by calculating the parasite prevalence in adult subjects (≥15 years) and child (≤15 years) as used by Simon et al.[7] The ACR of cases was calculated from total adult and child blood smear slide positive cases for the duration of the study period. Analysis of the malaria parasite species prevalence in the study sites was done using Chi-square statistic (χ2) while malaria infection rates between the sites and among age groups was analyzed by ANOVA.

  Results Top

Malaria parasite species prevalence

A total of 3880 individuals (2650 from Kapsisiywa and 1230 from Kipsamoite) aged from <1 year and above including males, females were screened for malaria from January to December 2014. The positivity rates (parasite ratio) of infection for the different malaria parasite species is shown in [Table 1]. Chi-square analysis indicated a significant difference (χ2, P < 0.05) between P. falciparum and P. malariae occurrence in the study sites. P. falciparum was the most prevalent malaria parasite accounting for 89.8% of the diagnosed cases in both study sites. P. malariae was recorded in both sites at low frequency and constituted 10.2% of malaria cases in Kapsisiywa and 9.8% in Kipsamoite [Table 1]. P. malariae was often seen in mixed infections with P. falciparum. No cases of P. vivax and P. ovale were detected. Malaria cases were more prevalent between the months of March to August during which about 95% of cases were recorded. The remaining 5% of the cases were detected in January and February. No malaria cases were recorded in October and December in both study sites.
Table 1: Plasmodium prevalence and parasite species prevalence

Click here to view

Adult and child vulnerability to malaria

The results [Figure 1] demonstrate that ACR in the study area ranged from 0.5 to 1 with an annual average of approximately 1 implying that malaria in the area was unstable. This was interpreted that there was an equivalent malaria risk in both adults and children. It also suggests that there is no community-acquired immunity.
Figure 1: The adult child ratios for Kapsisiywa and Kipsamoite in 2014 (KAPACR = Kapsisiywa adult child ratio, KIPACR = Kipsamoite adult child ratio, AVACR = Average Adult child ratio in the two study sites)

Click here to view

The average ACR of 0.84 (almost unity) further supports an even distribution of disease in both adults and children in the study sites. The annual ACR distribution also indicated that most positive cases were detected in the months of March to July, corresponding to the rainy season in the study sites.

  Discussion Top

Globally, there are five Plasmodium species that cause human malaria. These are: P. falciparum, P. malairae, P. vivax, P. ovale and Plasmodium knowlesi. The distribution and relative abundance in Kenya of four Plasmodium species that cause human malaria is as follows: P. falciparum is the most common (80–85%), P. malariae (10–15%), P. ovale (<5%), and with P. vivax reported as infrequent.

Of the 294 confirmed malaria cases in the study sites, 89.6–90.2% were P. falciparum and 9.8–10% P. malariae. The relatively short extrinsic incubation period of P. falciparum could be a possible reason to explain why the parasite species is more common than the others. Neither P. ovale nor P. vivax infections were detected. These results are consistent with those of others from the same or neighboring areas. Beier et al.[23] in a similar study in the lowlands of Kenya found equally higher rates for P. falciparum and lower rates in the other three malaria species.

P. falciparum is the parasite species responsible for the most serious forms of malarial illness and for essentially all fatal cases of the disease worldwide. The species has been associated with frequent malaria outbreaks in the Western Kenya highlands in the past.[7],[24],[25],[26] Since P. falciparum was the most prevalent in the present study area, efforts to limit mortality associated with it must be prioritized because of its potential fatal consequences. This suggests that any case of malaria encountered in the area and the study sites should receive effective treatment promptly and early enough to prevent severe disease, death, and spread. When falciparum malaria treatment is delayed or not given, there is danger of build-up of chronic infections in the population that eventually spread by the long-lived largely anthropophilic Anopheles gambiae vectors leading to outbreaks and possibility of epidemics.[27],[28],[29],[30] In a related study, in Western Kenya, Shanks et al.[31] key recommendation was to cure enough falciparum-infections to halt parasite spread during seasonal transmission. In this regard, the choice of the first line malaria therapy is crucial to cure those infected, as well as allow maximum number of persons to get access to free treatment.

The average calculated ACR ratios approximated unity, suggesting that malaria risk in childhood was comparable to that in adults (there were equivalent risk in children and adults). Such high ACR ratio indicates a less immune population in which both adults and children become symptomatic when infected with malaria parasite. In a related study in Uasin Gishu at an altitude of 2134 m, in Western Kenya, John et al.[10] found no difference in re-infection rates between children and adults indicating that transmission was unstable at that altitude.[32] This findings contrast with the age-related protection from infection reported in areas of stable, intense transmission.[33] It also demonstrates that areas of infrequent parasite exposure lend themselves to equivalent risk in adults and children.[7] This suggests an increasing tendency toward unstable malaria transmission, assuming that there were no age-dependent biases in clinic attendance rates at the sites.

The disease instability may further be explained by the hill valley topography common in the Western highlands. It is suggested to have an effect on malaria transmission intensity ranges from low to high.[34] In this regard, human settlers in the valley bottoms (near vector breeding sites) may serve as “malaria reservoirs,” experience more infective bites and they develop some degree of immunity to the severe consequences of malaria infection. This is the opposite of the human population uphill, which is not exposed to malaria infection regularly and generally lacks immunity to malaria because exposures are infrequent.[9] Therefore, the difference in exposure to infective bites of the general population may be the cause of disease transmission instability in this study sites and indeed in the entire Western highlands.

The discovery of clustered “hotspots” (defined as areas of high malaria incidence within an epidemic-prone area/clusters of cases of malaria within an epidemic prone zone) in study sites [17] could also explain the observed malaria transmission instability trend. The determinants of such clustered transmission spots are likely to be due to shared anthropogenic and environmental variables, as well as factors related to contagion such as population density and human settlements.[29]

In a related study,[35] findings demonstrated that there was spatial clustering of malaria cases in children during an epidemic in a single year in a highland area of Kenya. However, without sufficient data for several years, it is difficult to discern if the clusters of cases are transient or if they relate to more long-standing foci of infection that may affect the entire study area. The recognition of consistent foci of abundant vectors or malaria cases would permit focused control efforts to be directed at specific sites, reducing costs, and increasing effectiveness.[17]

The present epidemiological situation in the Western highlands may not remain so for long, because climatic change, topography, human settlement pattern, land use, and drug resistance may change the situation.[9] Climatic conditions influence the development, reproduction, and survivorship of anopheline mosquitoes and malaria parasites.[25] Topography and human settlement patterns affect the spatial distribution of vector mosquitoes and susceptible and immune populations.[36] Land use changes can cause the environmental conditions to be more favorable for the development and reproduction of mosquitoes and parasites.[37] Emergence of drug resistance aggravates malaria case fatality and enhances spread of resistant strains of parasites.[38] Therefore, future effective malaria control in the entire Western highlands will require an elaborate understanding of the interactions between and among these epidemiological factors.

  Conclusion Top

The most prevalent malaria parasite were P. falciparum and P. malariae Malaria parasite transmission was unstable and seasonal suggesting that residual immunity to disease diminished with time or did not develop with time. Based on these findings, malaria in the sample population had an even age distribution implying that the threat of epidemics was real when parasites are introduced and conditions of disease transmission become favorable.


The authors appreciate and thank all those who reviewed the paper and offered constructive suggestions.

The authors acknowledge all those who provided financial support that enabled us to undertake the study.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Fontenille D, Simard F. Unravelling complexities in human malaria transmission dynamics in Africa through a comprehensive knowledge of vector populations. Comp Immunol Microbiol Infect Dis 2004;27:357-75.  Back to cited text no. 1
Guyatt HL, Corlett SK, Robinson TP, Ochola SA, Snow RW. Malaria prevention in highland Kenya: Indoor residual house-spraying vs. insecticide-treated bednets. Trop Med Int Health 2002;7:298-303.  Back to cited text no. 2
Garnham PC. The incidence of malaria at high altitudes. J Natl Malar Soc 1948;7:275-84.  Back to cited text no. 3
Matson AT. The history of malaria in Nandi. East Afr Med J 1957;34:431-41.  Back to cited text no. 4
Roberts JM. The control of epidemic malaria in the highlands of Western Kenya. II. The campaign. J Trop Med Hyg 1964;67:191-9.  Back to cited text no. 5
Cox J, Sharp B. Mapping Malaria Risk in African Highlands. MIMMalaria Conference in conjunction with Southern African Malaria Conference and Roll Back Malaria Project, International Convention Centre (ICC), Durban South Africa; 1999. p. B-20.  Back to cited text no. 6
Hay SI, Simba M, Busolo M, Noor AM, Guyatt HL, Ochola SA, et al. Defining and detecting malaria epidemics in the highlands of Western Kenya. Emerg Infect Dis 2002;8:555-62.  Back to cited text no. 7
World Health Organization. Frequently Asked Questions on DDT use for disease Vector Control. Document: WHO/HTM/RBM/2004.54. Geneva, Switzerland: World Health Organization; 2004.  Back to cited text no. 8
Zhou G, Minakawa N, Githeko AK, Yan G. Association between climate variability and malaria epidemics in the east African highlands. Proc Natl Acad Sci U S A 2004;101:2375-80.  Back to cited text no. 9
Carlson JC, Byrd BD, Omlin FX. Field assessments in Western Kenya link malaria vectors to environmentally disturbed habitats during the dry season. BMC Public Health 2004;4:33.  Back to cited text no. 10
Shanks GD, Biomndo K, Guyatt HL, Snow RW. Travel as a risk factor for uncomplicated Plasmodium falciparum malaria in the highlands of Western Kenya. Trans R Soc Trop Med Hyg 2005;99:71-4.  Back to cited text no. 11
Allan R, Nam S, Doull L. Merlin and malaria epidemic in North-East Kenya. Lancet 1998;351:1966-7.  Back to cited text no. 12
Pascual M, Ahumada JA, Chaves LF, Rodó X, Bouma M. Malaria resurgence in the East African highlands: Temperature trends revisited. Proc Natl Acad Sci U S A 2006;103:5829-34.  Back to cited text no. 13
Pascal M, Jonathan A, Olson SH. Malaria risk and temperature: Influences from global climate change and local land- use practices. Proc Natl Acad Sci 2006;103:5633-34. Available from: http://www.pubmedcentral.nih.gov. [Last accessed on 2006 Apr 11].  Back to cited text no. 14
Omar SA, Adagu IS, Gump DW, Ndaru NP, Warhurst DC. Plasmodium falciparum in Kenya: High prevalence of drug-resistance-associated polymorphisms in hospital admissions with severe malaria in an epidemic area. Ann Trop Med Parasitol 2001;95:661-9.  Back to cited text no. 15
John CC, Ouma JH, Sumba PO, Hollingdale MR, Kazura JW, King CL. Lymphocyte proliferation and antibody responses to Plasmodium falciparum liver-stage antigen-1 in a highland area of Kenya with seasonal variation in malaria transmission. Am J Trop Med Hyg 2002;66:372-8.  Back to cited text no. 16
Ernst KC, Adoka SO, Kowuor DO, Wilson ML, John CC. Malaria hotspot areas in a highland Kenya site are consistent in epidemic and non-epidemic years and are associated with ecological factors. Malar J 2006;5:78.  Back to cited text no. 17
World Health Organization. Global Malaria Programme 1998, (WHO/MAL/98.1084). Geneva: WHO; 1998.  Back to cited text no. 18
Najera JA, Kouznetsov RL, Delacotte C. Malaria Epidemics Detection and Control Forecasting and Prevention. WHO Document, WHO/MAL/98.1084. Geneva, Switzerland: WHO; 1998.  Back to cited text no. 19
Roll Back Malaria/World Health Organization. Malaria Early Warning Systems: Concepts, Indicators and Partners. A Framework for Field Research in Africa. Document. WHO/CDS/RBM/2001.32. Geneva, Switzerland: World Health Organization; 2001.  Back to cited text no. 20
Mulambalah CS, Siamba DN, Ngeiywa MM, Vulule JM. Diversity of Anopheles species and prevalence of malaria in a highland area of Western Kenya. J Parasitol Vector Biol 2011;3:33-9.  Back to cited text no. 21
Prybylski D, Khaliq A, Fox E, Sarwari AR, Strickland GT. Parasite density and malaria morbidity in the Pakistani Punjab. Am J Trop Med Hyg 1999;61:791-801.  Back to cited text no. 22
Beier JC, Perkins PV, Wirtz RA, Koros J, Diggs D, Gargan TP 2nd, et al. Bloodmeal identification by direct enzyme-linked immunosorbent assay (ELISA), tested on Anopheles (Diptera: Culicidae) in Kenya. J Med Entomol 1988;25:9-16.  Back to cited text no. 23
Some ES. Effects and control of highland malaria epidemic in Uasin Gishu district, Kenya. East Afr Med J 1994;71:2-8.  Back to cited text no. 24
Githeko A, Ndegwa W. Predicting malaria epidemics using climate data in Kenyan highlands: A tool for decision makers. Glob Change Hum Health 2001;2:54-63.  Back to cited text no. 25
Hay SI, Cox J, Rogers DJ, Randolph SE, Stern DI, Shanks GD, et al. Climate change and the resurgence of malaria in the East African highlands. Nature 2002;415:905-9.  Back to cited text no. 26
Beier JC, Killeen GF, Githure JI. Short report: Entomologic inoculation rates and Plasmodium falciparum malaria prevalence in Africa. Am J Trop Med Hyg 1999;61:109-13.  Back to cited text no. 27
Marsh K, Snow RW. Malaria transmission and morbidity. Parassitologia 1999;41:241-6.  Back to cited text no. 28
Carter R, Mendis KN, Roberts D. Spatial targeting of interventions against malaria. Bull World Health Organ 2000;78:1401-11.  Back to cited text no. 29
Killeen GF, McKenzie FE, Foy BD, Schieffelin C, Billingsley PF, Beier JC. The potential impacts of integrated malaria transmission control on entomologic inoculation rate in highly endemic areas. Am J Trop Med Hyg 2000;62:545-51.  Back to cited text no. 30
Shanks GD, Hay SI, Omumbo JA, Snow RW. Malaria in Kenya's Western highlands. Emerg Infect Dis 2005;11:1425-7.  Back to cited text no. 31
Otsyula GM, Githeko AK, Zhou G, Mushinzimana E, Minakawa N, Yan G. plasmodium falciparum spatial analysis, Western Kenya highlands. Emerg Infect Dis 2005;11:1-13.  Back to cited text no. 32
John CC, Koech DK, Sumba PO, Ouma JH. Risk of Plasmodium falciparum infection during a malaria epidemic in highland Kenya, 1997. Acta Trop 1997;92:55-61.  Back to cited text no. 33
Lindsay SW, Martens WJ. Malaria in the African highlands: Past, present and future. Bull World Health Organ 1998;76:33-45.  Back to cited text no. 34
Brooker S, Clarke S, Njagi JK, Polack S, Mugo B, Estambale B, et al. Spatial clustering of malaria and associated risk factors during an epidemic in a highland area of Western Kenya. Trop Med Int Health 2004;9:757-66.  Back to cited text no. 35
Balls MJ, Bødker R, Thomas CJ, Kisinza W, Msangeni HA, Lindsay SW. Effect of topography on the risk of malaria infection in the Usambara mountains, Tanzania. Trans R Soc Trop Med Hyg 2004;98:400-8.  Back to cited text no. 36
Lindblade KA, Walker ED, Onapa AW, Katungu J, Wilson ML. Land use change alters malaria transmission parameters by modifying temperature in a highland area of Uganda. Trop Med Int Health 2000;5:263-74.  Back to cited text no. 37
Githeko AK, Lindsay SW, Confalonieri UE, Patz JA. Climate change and vector-borne diseases: A regional analysis. Bull World Health Organ 2000;78:1136-47.  Back to cited text no. 38


  [Figure 1]

  [Table 1]

This article has been cited by
1 Potential distribution of the primary malaria vector Anopheles gambiae Giles [Diptera: Culicidae] in Southwest Nigeria under current and future climatic conditions
Isaac Omotayo Olabimi, Kayode David Ileke, Babasola Williams Adu, Temitope Emmanuel Arotolu
The Journal of Basic and Applied Zoology. 2021; 82(1)
[Pubmed] | [DOI]
2 Dominant malaria vector species in Nigeria: Modelling potential distribution of Anopheles gambiae sensu lato and its siblings with MaxEnt
Godwin E. Akpan,Kayode A. Adepoju,Olakunle R. Oladosu,Samuel A. Adelabu,Aysegul Taylan Ozkan
PLOS ONE. 2018; 13(10): e0204233
[Pubmed] | [DOI]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Subjects and Methods
Article Figures
Article Tables

 Article Access Statistics
    PDF Downloaded286    
    Comments [Add]    
    Cited by others 2    

Recommend this journal