Malaria Case Presentation: The Results of a Web Based
Malaria Surveillance in Plateau State, Nigeria

Mafuyai H. B.; Tanko I.; Oguche S.; Egah D. Envuladu E.A.; Mwansat G.S.; Pam D. D.; Shwe D.; Nannvyat N.; Oguche D.; Barshep Y.

doi:https://www.doi.org/10.56201/ijmepr.v6.no1.2022.pg13.22

Malaria Case Presentation: The Results of a Web Based Malaria Surveillance in Plateau State, Nigeria

Mafuyai H. B., Tanko I., Oguche S., Egah D. Envuladu E.A., Mwansat G.S., Pam D. D., Shwe D., Nannvyat N., Oguche D., Barshep Y.

Abstract

Nigeria bears the heaviest malaria burden of any single nation in the world and has relentlessly pursued the elimination of the disease. One of the key strategies for the elimination of malaria is increasing the specificity and sensitivity of surveillance. To this end, this study sought to determine malaria transmission along an altitudinal gradient of Plateau state, central Nigeria, while examining socio- demographic factors affecting the prevalence of malaria at these sites. Three communities each at high and low elevation areas of Plateau State in central Nigeria were surveyed for incidence of malaria cases. Information on age, gender, use of long-lasting insecticide treated nets, pregnancy status in women, and, malaria severity were recorded in 1700 study subjects. Using venipuncture method, 4ml blood samples were collected in EDTA vials for laboratory analyses. Microscopy (thick and thin blood smear techniques) and Rapid Diagnostic test were used to detect malaria parasites and determine the Plasmodium species involved. Using a propriety application (ELDACAP), real time geolocation data, socioeconomic, health, and preventative status information were also collected from all 1700 respondents. Our findings showed more cases of malaria prevalence in lowland areas compared to highland areas. The main predictors of malaria incidence were age, sex, use of ITN and the presentation of symptoms. Non-net users had more prevalence of malaria compared to users, males had a higher positive frequency compared to females, and malaria was more prevalent in the younger age group compared to older group. Malaria eradication in north-central Nigeria must take into account geographic differences, cultural and social practices, previous anti-malaria preventative measures (use of ITN), as well as the presence of asymptomatic malaria carriers who serve as reservoir in the population.

Keywords

MalariaSurveillancealtitudecentral Nigeria

References

Adigun, A. B., Gajere, E. N., Oresanya, O., & Vounatsou, P. (2015). Malaria risk in Nigeria: Bayesian geostatistical modelling of 2010 malaria indicator survey data. Malaria Journal, 14(1), 1–8. https://doi.org/10.1186/s12936-015-0683-6 Bartoloni, A., & Zammarchi, L. (2012). Clinical aspects of uncomplicated and severe malaria. Mediterranean Journal of Hematology and Infectious Diseases, 4(1). https://doi.org/10.4084/MJHID.2012.026 Bassey, S. E., & Izah, S. C. (2017). Some Determinant Factors of Malaria Prevalence in Nigeria. Journal of Mosquito Research, July. https://doi.org/10.5376/jmr.2017.07.0007 Gosoniu, L., Msengwa, A., Lengeler, C., & Vounatsou, P. (2012). Spatially explicit Burden estimates of malaria in Tanzania: Bayesian geostatistical modeling of the malaria indicator survey data. PLoS ONE, 7(5). https://doi.org/10.1371/journal.pone.0023966 Jenkins, R., Omollo, R., Ongecha, M., Sifuna, P., Othieno, C., Ongeri, L., Kingora, J., & Ogutu, B. (2015). Prevalence of malaria parasites in adults and its determinants in malaria endemic area of Kisumu County, Kenya. Malaria Journal, 14(1). https://doi.org/10.1186/s12936-015-0781-5 Messina, J. P., Taylor, S. M., Meshnick, S. R., Linke, A. M., Tshefu, A. K., Atua, B., Mwandagalirwa, K., & Emch, M. (2011). Population, behavioural and environmental drivers of malaria prevalence in the Democratic Republic of Congo. Malaria Journal, 10(1), 161. https://doi.org/10.1186/1475-2875-10-161 Nanvyat, N., Mulambalah, C., Barshep, Y., Ajiji, J., Dakul, D., & Tsingalia, H. (2018). Malaria transmission trends and its lagged association with climatic factors in the highlands of Plateau State, Nigeria. Tropical Parasitology, 8(1). https://doi.org/10.4103/tp.TP_35_17 Nanvyat, Nannim, Siteti Mulambalah, C., Barshep, Y., Mugatsia Tsingalia, H., & Anthony Dakul, an. (2017). Retrospective analysis of malaria transmission patterns and its association with meteorological variables in lowland areas of Plateau state, Nigeria. ~ 101 ~ International Journal of Mosquito Research, 4(4), 101–106. NMIS, & NPC. (2010). National Malaria Indicator Survey (NMIS) 2010. R Development Core Team. (2019). R Development Core Team. In R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.mendeley.com/research/r- language-environment-statistical- computing-96/%5Cnpapers2://publication/uuid/A1207DAB-22D3-4A04-82FB- D4DD5AD57C28 Tesfaye, S., Belyhun, Y., Teklu, T., Mengesha, T., & Petros, B. (2011). Malaria prevalence pattern observed in the highland fringe of Butajira, Southern Ethiopia: A longitudinal study from parasitological and entomological survey. Malaria Journal, 10, 1–9. https://doi.org/10.1186/1475-2875-10-153 World Health Organization. (2020). World Malaria Report: 20 years of global progress and challenges. In World Health Organization. https://www.who.int/publications/i/item/9789240015791 Woyessa, A., Deressa, W., Ali, A., & Lindtjørn, B. (2012). Prevalence of malaria infection in Butajira area, south-central Ethiopia. Malaria Journal, 11, 1–8. https://doi.org/10.1186/1475-2875-11-84

Malaria Case Presentation: The Results of a Web Based Malaria Surveillance in Plateau State, Nigeria

Abstract

Keywords

References

More Articles from INTERNATIONAL JOURNAL OF MEDICAL EVALUATION AND PHYSICAL REPORT