GIS-based spatiotemporal mapping of malaria prevalence and exploration of environmental inequalities.

Malaria poses a significant threat to global health, with particular severity in Nigeria. Understanding key factors influencing health outcomes is crucial for addressing health disparities. Disease mapping plays a vital role in assessing the geographical distribution of diseases and has been instrumental in epidemiological research. By delving into the spatiotemporal dynamics of malaria trends, valuable insights can be gained into population dynamics, leading to more informed spatial management decisions. This study focused on examining the evolution of malaria in Nigeria over twenty years (2000-2020) and exploring the impact of environmental factors on this variation. A 5-year-period raster map was developed using malaria indicator survey data for Nigeria's six geopolitical zones. Various spatial analysis techniques, such as point density, spatial autocorrelation, and hotspot analysis, were employed to analyze spatial patterns. Additionally, statistical methods, including Principal Component Analysis, Spearman correlation, and Ordinary Least Squares (OLS) regression, were used to investigate relationships between indicators and develop a predictive model. The study revealed regional variations in malaria prevalence over time, with the highest number of cases concentrated in northern Nigeria. The raster map illustrated a shift in the distribution of malaria cases over the five years. Environmental factors such as the Enhanced Vegetation Index, annual land surface temperature, and precipitation exhibited a strong positive association with malaria cases in the OLS model. Conversely, insecticide-treated bed net coverage and mean temperature negatively correlated with malaria cases in the same model. The findings from this research provide valuable insights into the spatiotemporal patterns of malaria in Nigeria and highlight the significant role of environmental drivers in influencing disease transmission. This scientific knowledge can inform policymakers and aid in developing targeted interventions to combat malaria effectively.

Under age five children survival times in Nigeria: a Bayesian spatial modeling approach.

BACKGROUND: Nigeria is among the top five countries in the world with the highest under-five mortality rates. In addition to the general leading causes of under-five mortality, studies have shown that disparity in sociocultural values and practices across ethnic groups in Nigeria influence child survival, thus there is a need for scientific validation. This study quantified the survival probabilities and the impact of socioeconomic and demographic factors, proximate and biological determinants, and environmental factors on the risk of under-five mortality in Nigeria. METHODS: The Kaplan-Meier survival curve, Nelson Aalen hazard curve, and components survival probabilities were estimated. The Exponential, Gamma, Log-normal, Weibull, and Cox hazard models in a Bayesian mixed effect hierarchical hazard modeling framework with spatial components were considered, and the Deviance and Watanabe Akaike information criteria were used to select the best model for inference. A [Formula: see text] level of significance was assumed throughout this work. The 2018 Nigeria Demographic and Health Survey dataset was used, and the outcome variable was the time between birth and death or birth and the date of interview for children who were alive on the day of the interview. RESULTS: Findings show that the probability of a child dying within the first two months is 0.04, and the probability of a boy child dying before attaining age five is 0.106, while a girl child is 0.094 probability. Gender, maternal education, household wealth status, source of water and toilet facility, residence, mass media, frequency of antenatal and postnatal visits, marital status, place of delivery, multiple births, who decide healthcare use, use of bednet are significant risk factors of child mortality in Nigeria. The mortality risk is high among the maternal age group below 24 and above 44years, and birth weight below 2.5Kg and above 4.5Kg. The under-five mortality risk is severe in Kebbi, Kaduna, Jigawa, Adamawa, Gombe, Kano, Kogi, Nasarawa, Plateau, and Sokoto states in Nigeria. CONCLUSION: This study accentuates the need for special attention for the first two months after childbirth as it is the age group with the highest expected mortality. A practicable way to minimize death in the early life of children is to improve maternal healthcare service, promote maternal education, encourage delivery in healthcare facilities, positive parental attitude to support multiple births, poverty alleviation programs for the less privileged, and a prioritized intervention to Northern Nigeria.

Spatial pattern and determinants of anemia among women of childbearing age in Nigeria.

BACKGROUND: The risk of anemia in Nigeria is of public health importance, with an increasing number of women of reproductive age being anemic. This study sought to identify the spatial distribution and examine the geographical variation of anemia risk at a regional level while accounting for risk factors associated with anemia among women of childbearing age in Nigeria. The significant interest in spatial statistics lies in identifying associated risk factors that enhance the risk of infection. However, most studies make no or limited use of the data's spatial structure and possible non-linear effects of the risk factors. METHODS: The data used in this study were extracted from the 2015 Nigeria Demographic and Health Survey (NDHS). A full Bayesian semi-parametric regression model was fitted to data to accomplish the aims of the study. Model estimation and the inference was fully Bayesian approach via integrated nested Laplace approximations (INLA). The fixed effects were modeled parametrically; non-linear effects were modeled non-parametrically using second-order random walk priors. RESULTS: Wealth index, level of education, type of residence, and unprotected drinking water source were found to be the risk factors associated with anemia. The risk of anemia was found to vary across different regions, with North Central, North East, and North West regions having the highest number of cases and South East with the least number of cases. The spatial analysis result indicated that statistically high hot-spots of anemia were observed in all the northern parts of the country. CONCLUSION: The study revealed associations between anemia risk and women residing in rural settlements, wealth index, women with no formal education, and unprotected drinking water sources. Community and household-related change interventions should, therefore, be pertinent to the prevention of anemia. The spatial analysis further revealed a significant anemia risk towards the Northern areas of Nigeria. We propose that interventions targeting women of reproductive age should initially focus on these regions and subsequently spread across Nigeria.

Statistical Modeling of Determinants of Anemia Prevalence among Children Aged 6-59 Months in Nigeria: A Cross-Sectional Study.

OBJECTIVE: Childhood anemia remains a significant public health challenge in developing countries, and it has negative consequences on the growth of the children. Therefore, it is essential to identify the determinants of childhood anemia, as these will help in formulating appropriate health policies in order to meet the United Nations MDG goal. This study aims to assess and model the determinants of the prevalence of anemia among children aged 6-59 months in Nigeria. To accomplish the aims of the study, the authors applied single-level and multilevel binary logistic regression models. METHODS: To measure the relative impact of individual and household-level factors for childhood anemia among children aged 6-59 months, this study undertakes data from Nigeria Demographic and Health Surveys with both binary logistic and multilevel logistic regression models. The fit of the model was assessed by Hosmer-Lemeshow goodness-of-fit, variance inflation factor, and likelihood ratio tests. RESULTS: The study established that about 67.01% of the children were anemic and identified sex of children, mother's education, religion, household wealth status, total children ever born, age of children, place of residence, and region to have a statistical significant effect on the prevalence of anemia. The adjusted odds ratio (aOR) for anemia was 0.56 (95% CI = 0.50, 0.63) in children aged from 24 to 42 months and 0.40 (95% CI = 0.36, 0.45) in children aged from 43 to 59 months. Also, children who reside in certain geographical-political zones of Nigeria are associated with increased childhood anemia. CONCLUSION: This study has highlighted the high prevalence of childhood anemia in Nigeria and indicated the need to improve mothers' education and regional variations. Findings from this study can help policymakers and public health institutions to map out programs targeting these regions as a measure of tackling the prevalence of anemia among the Nigerian populace.