No abstract

Aim: To investigate the prevalence of malaria and how demographic factors influence malaria parasite transmission among persons attending primary health care facilities in Oyigbo LGA, Rivers State, South-South, Nigeria. Methodology: Intra-venous blood samples were obtained from 190 participants who enrolled for the study. These blood samples were stored in ethylene diamine tetra acetate bottles (EDTA) and used to make thick and thin films for malaria parasite detection using standard parasitological techniques (Cheesbrough 1998). Questionnaires were administered to the participants to obtain their demographic data. Data were analysed using the Statistical Package for Social Sciences version 25 and presented using descriptive statistics. Chi-square was used to obtain level of significance (p<0.05). Results: Of the 190 persons examined, 109 were positive, giving a prevalence of 57.4%. Plasmodium falciparum was the only malaria parasite observed. Females 67 (59.82%) were more affected than males 42 (53.84%) but this difference was not statistically significant (p>0.05). Age group 41-50 and those with Secondary education had higher prevalence. The difference observed in these groups was statistically significant (p<0.05). Artisans had the highest prevalence whereas the unemployed had the least prevalence. However, this difference was not statistically significant (p>0.05). Conclusion: Demographic factors have been shown to influence malaria transmission. Therefore, malaria control efforts should be intensified, taking into cognizance, the role of demographic factors in transmission.

Background: Variations in the risk of malaria across locations exist but are poorly understood though identifying hotspots of malaria transmission will create opportunities for targeted interventions. Point prevalence of malaria in Rivers State was studied using Primary Healthcare Centres (PHCs) as survey points. Methods: The PHCs in Rivers State were geo-referenced using a handheld Global Positioning System (GPS) and 74 were selected across 21 local government areas using systematic grid point sampling. Blood samples were obtained from 2340 persons who consented and questionnaires were administered to obtain their demographic data. Malaria parasites in blood films were detected using the Giemsa staining technique. Data generated were analysed using SPSS 22.0 and presented using descriptive statistics. The level of relationship amongst the parameters was obtained using Chi-square. Co-ordinates of PHCs sampled and their prevalence data for malaria were entered into Microsoft Excel 2007 spreadsheet and transmitted to ArcGIS 10.8. This platform was then used to produce point prevalence infection maps of the State using geographic information systems (GIS). Survey points with malaria point prevalence values of 75% and above and cumulative prevalence of 1.97% and above were categorised as malaria transmission hot spots in the various LGAs. Results: The study recorded an overall prevalence of 56.3%, with P.falciparum as the only identified malaria parasite. Data revealed that Oyoro Model Primary Health Centre (MPHC), Arukwo Primary Health Centre, Ele Health Post (HP) and Emago HP recorded very high prevalence of 96.7%, 96%, 95.2% and 94.4% respectively, whereas MPHC Iriebe had the least prevalence. Twelve hotspots with point prevalence above 75% were identified and eight hotspots likewise with cumulative prevalence above 1.97%. Conclusion: Malaria infection remains endemic in Rivers State. This study provides malaria point prevalence maps of Rivers State which will serve as a reference to policymakers for strategic interventions in the State

The study used a retrospective design to examine the temporal patterns of malaria morbidity in Oyigbo LGA and investigate the relationship between temperature and rainfall on patterns of malaria morbidity in Oyigbo L.G.A. from 2007-2017. Malaria morbidity data from 2007 to 2017 were obtained from the Integrated Disease Surveillance and Response System of Rivers State Ministry of Health while temperature and rainfall records from year 2007 to 2017 were obtained from Nigeria Meteorological Agency (NIMET), Abuja. Data generated were analyzed using SPSS 22.0 and presented using descriptive and inferential statistics. A total of 43,662 malaria cases was recorded in the study area within during the study period with mean morbidity of 330.77. Mean temperature of 27.32 o C and mean rainfall of 137.13mm were recorded. Temperature showed a negative relationship with malaria which was significant in the years 2012 and 2014. Rainfall and morbidity showed a positive relationship which was significant only in year 2012. Across the months, temperature and malaria morbidity showed a negative insignificant relationship. However, rainfall showed a positive and significant relationship with malaria morbidity in May. Malaria remains endemic among the local subjects in the study area. During the study period, overall study showed no significant relationship between malaria morbidity, temperature and rainfall. This is to say that climatic variables are not the major drivers of malaria morbidity in the study area. It is therefore recommended that more epidemiological studies be carried out to determine the drivers of malaria transmission to aid evidence-based interventions