2014.ISDS.Abstracts.Final.pdf ISDS Annual Conference Proceedings 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution- Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ISDS 2014 Conference Abstracts Insight into Malaria Transmission and Control in Endemic Areas Beatty V. Maikai*1, Jarlath U. Umoh1 and Victor A. Maikai2 1Department of Veterinary Public Health and Preventive Medicine, Faculty of Veterinary Medicine, Ahmadu Bello University, Zaria, Nigeria; 2College of Agriculture and Animal Science, Ahmadu Bello University, Kaduna, Nigeria Objective To examine the likely impact of malaria parasite intervention points for a steady state regional control program in endemic areas Introduction The global effort of malaria control is in line with the one world one health concept, but then a globally defined ‘‘one-size-fits-all’’ malaria control strategy would be inefficient in endemic areas. Plasmodium falciparum is the type of malaria parasite that most often causes severe and life-threatening malaria. People get malaria by being bitten by an infective female Anopheles mosquito. Regional malaria elimination campaigns in 1940s followed by the Global Malaria Eradication Program in 1955 did not succeed in eliminating malaria from sub- Saharan Africa, which accounts for 80% of today’s burden of malaria (1,2). The basic reproductive number, Ro, has played a central role in epidemiological theory for malaria and other infectious diseases because it provides an index of transmission intensity and establishes threshold criteria (3). Methods Use of systematic literature review to propose a simple model on the likely impact of targeted intervention points on control of malaria parasite. Assumptions were varied about two targeted epidemiologic control points on the basic reproductive number, Ro, which is affected by different factors and upon which the status of malaria in any community will depend. Taking to be expected number of infectious bites per person over a given time period; 1 as the effective contact between susceptible individuals and malaria vectors; 2 as the effective contact between individuals under intervention and malaria vectors; 3 as the effective contact between susceptible malaria vectors and infected individuals; S= susceptible population, V= population under intervention, D= dead mosquitoes and R= immune humans. At any time t in a population, j, vectoral capacity C(t) = mj (t) aj 2 pj n/(-ln pj) ( 4); infected human j=1 population at intervention point, Ih(t)=C(t) ( 1Sh + (1 – ) 2V) - R; infected mosquito population at intervention point, Im(t)= (1 – ) 3Sm(C(t)). If is the degree of protective intervention, which is also equal to 1. Thus 1 - is the intervention failure. Intervention will reduce the probability of infection when exposed to malaria pathogens and this equals the degree of protection = Ih(t)/ Im(t); Ro 1/ ; Ro= b/ where b is infectivity of humans to mosquitoes. Results Population important in malaria transmission are the susceptible, infected and infectious Anopheles mosquitoes and human populations. Three factors in this basic model that can affect Ro are the infectivity of humans, b, the effective or adequate contact between vector and individuals, , and the vectoral capacity, C(t). Increase in Ro will inversely decrease . For there to be decrease in Ro, control has to be effective. When there is interventions targeted at reducing density of mosquitoes and humans through destruction of breeding sites and prophylaxis/treatment/use of nets respectively over a given time period, number infected will be immuned at which point, Ro = 1, more immune individuals wil llead to Ro1 until when there is a steady state control program at which point Ro=0. This is the point that intervention is very effective. Conclusions The two targeted control points should be considered for any effective malaria control and eradication program in endemic areas so that Ro can be consistently lowered to a level that is below threshold. Keywords Malaria; Control; Endemic References 1.Carter, R, Mendis KN. Evolutionary and historical aspects of the burden of malaria. Clin Microbiol Rev 2002; 15: 564-94. 2.Lopez AD, Mathers CD, Ezzati M, Murray ChJL. Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. Lancet 2006; 367: 1747-57. 3.Hadeler KP, and Castillo-Chavez C. A Core Group Model for Disease Transmission, Mathematical Biosciences 1995; 128: 41-55. 4. Garrett-Jones C. Prognosis for interruption of malaria transmission through assessment of the mosquito’s vectorial capacity. Nature 1964; 204: 1173–1175 *Beatty V. Maikai E-mail: Beatt18@yahoo.com Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * (1):e198, 201