Malaria Parasitaemia amongst Military Personnel Households in a Military Formation in Port Harcourt, Nigeria

Egbom, Sylvia; Nzeako, Sidney O.

doi:10.12983/ijsres-2017-p0010-0016

Cited by 6 publications

(7 citation statements)

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“…The study revealed an overall malaria prevalence of 56.3% in the various PHCs sampled in the study area. The result is in line with the accounts of Egbom and Nzeako (2017) and Egbom et al, (2021), who recorded the prevalence of 52.5% and 57.4%, respectively in Rivers State. The reason for the relatively high prevalence could be connected to the existing environmental conditions that may have enabled stable malaria transmission or the common day-to-day practices of the inhabitants that could continuously make them susceptible to the bites of the vectors.…”

Section: Discussionsupporting

confidence: 91%

“…Gender-related prevalence showed that both genders were affected equally, with males and females recording 56.3% and 56.27%, respectively. This is in contrast with the findings of Amadi et al (2011), Chijioke-Nwauche and Sam-Ozini (2017), Egbom and Nzeako (2017), Egbom et al 2021 andOkonko et al (2021) who recorded higher prevalence among the females and the reports of Abah et al (2017) and Wokem et al (2020) who reported higher prevalence among the males. This could be because most of the participants in this study live in rural communities where they were equally exposed to the bites of mosquitoes due to their habits.…”

Section: Discussioncontrasting

confidence: 74%

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Point prevalence mapping of malaria infection in Rivers State, Nigeria

Egbom¹,

Nduka

Nzeako

2022

Tanzania J Hlth Res

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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

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Section: Discussionsupporting

confidence: 91%

Section: Discussioncontrasting

confidence: 74%

Point prevalence mapping of malaria infection in Rivers State, Nigeria

Egbom¹,

Nduka

Nzeako

2022

Tanzania J Hlth Res

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“…Rivers State, in Nigeria's Niger Delta region, is one of the states having a high incidence of malaria cases. Malaria remains endemic in Rivers State [6], [7], [8], [9], [10], [11] with spatiotemporal variations reported [12]. It is a major source of illness and death in Rivers State, despite the availability of efficacious interventions.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Interplay of Meteorological Variables, Government Policies, and Malaria Epidemiology: Towards an Optimal Predictive Model for Malaria Spread in Rivers State, Nigeria

Egbom,

Nduka,

Nzeako

et al. 2024

Preprint

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Background: Malaria continues to be a serious public health issue, especially in tropical and subtropical areas where the dynamics of its transmission are greatly influenced by environmental conditions. The objective of this research is to examine the impact of meteorological factors, and governmental policies on malaria epidemiology to determine the most effective model for forecasting and comprehending the transmission of malaria in Rivers State, Nigeria. Method: Three statistical models for count data were compared to identify the most influential meteorological variables and government policy and establish their associations with malaria transmission. The best count data model was compared with a seasonal autoregressive integrated moving average model using some known model evaluation metrics. Results: The results obtained showed that the best count data model out of the two models considered in this study is the Quasi-Poisson Model because it resulted in a smaller Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) value. The SARIMAX Model outperformed the Quasi-Poisson model and showed that season, precipitation and government policies were significant at a 5% level of significance in explaining the variations in the monthly number of malaria cases in Rivers State, Nigeria (Jan. 2007 – Dec. 2021). Further, the SARIMAX (1,1,0)(1,1,1)12 model showed that the current number of malaria cases depends on the past year’s number of cases. Conclusion: The findings of this study highlight the need for a multifaceted approach to malaria control in Rivers State, addressing not only the meteorological factors but also the governance-related determinant of the disease. The identified optimal model serves as a valuable resource for policymakers, researchers, and healthcare practitioners, enabling them to make informed decisions and implement targeted interventions to mitigate the impact of malaria outbreaks.

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“…P. falciparum and P. vivax causes the most serious and virulent form of the disease (Joseph et al, 2011). The disease is transmitted by female Anopheles mosquitoes which feed between dusk and dawn (Egbom and Nzeako, 2017). In 2019, 229 million new cases and approximate 409,000 deaths were recorded (WHO, 2021).…”

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confidence: 99%

Malaria Parasitaemia and Intervention Measures amongst Pregnant Women in Delta State, Nigeria

O.¹,

Nduka²,

Nzeako³

2021

theijst

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Malaria is a disease that infects the red blood cells and liver caused by five sibling species of Apicomplexan protozoan of the genus; Plasmodium (Egbom and Nzeako, 2017). P. falciparum, P. vivax, P. malariae and P. ovale are specific to humans and in recent yearsP. knowlesi which is a species of Plasmodium that causes malaria among monkeys. P. falciparum and P. vivax causes the most serious and virulent form of the disease (Joseph et al., 2011). The disease is transmitted by female Anopheles mosquitoes which feed between dusk and dawn (Egbom and Nzeako, 2017). In 2019, 229 million new cases and approximate 409,000 deaths were recorded (WHO, 2021). On a global scale, over two third of malaria deaths occur in children under the age of five and pregnant women. Almost 1 out of 5 deaths of children under 5 years in Africa is due to malaria and this accounts for 67% (274,000) of all malaria deaths world-wide (WHO, 2021). World Health Organization defines malaria as a disease of poverty caused by poverty (Schantz -Dunn and Nawal, 2009), a strong correlativity exists between malaria and poverty, not only does malaria thrive in poverty but, also impedes economic growth and keeps households in poverty (Teklehaimanot and Mejia, 2008).The number of malaria cases seems to be increasing; due to increased transmission risks in areas where malaria control has declined, and the development of drug resistant strains of the parasite and in few cases, massive increases in international travel and migration (Pasvol, 2005). The reduction of immunity in pregnant women and immature level of immunity of children under the ages of 0-5 years often predisposes them to malaria infection (Fievetet al., 2007; Omanget al.,2020; Wogu and Onosakponome, 2020). Malaria infection during pregnancy is an important public health problem with increased risk for the pregnant women, her fetus and the new born child (Omanget al., 2020). It is hypothesized that the majority of sequelae in pregnancy results from two main factors: the immune-compromised stated of pregnancy and placental sequestration of infected erythrocytes (Schantz -Dunn and Nawal, 2009).Malaria in pregnancy contributes to high morbidity, 2-15% maternal anemia, 6 -14% low birth weight, 8-36% of preterm birth,13-70% of intrauterine growth retardation, 3 -8% of infant death and 2-15% of maternal anemia (ASPAD, 2004).

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Malaria Parasitaemia amongst Military Personnel Households in a Military Formation in Port Harcourt, Nigeria

Cited by 6 publications

References 0 publications

Point prevalence mapping of malaria infection in Rivers State, Nigeria

Point prevalence mapping of malaria infection in Rivers State, Nigeria

Exploring the Interplay of Meteorological Variables, Government Policies, and Malaria Epidemiology: Towards an Optimal Predictive Model for Malaria Spread in Rivers State, Nigeria

Malaria Parasitaemia and Intervention Measures amongst Pregnant Women in Delta State, Nigeria

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