Background and objectiveUse of insecticide treated nets (ITN), one of the most cost-effective malaria interventions contributes to malaria cases averted and reduction in child mortality. We explored ...the use of ITN in children under five (CU5) and children of school age to understand factors contributing to ITN use.MethodsA cross-sectional study analyzed 2018 Nigeria Demographic and Health Survey data. The outcome variable was CU5 or children of school age who slept under ITN the night before the survey. Independent variables include child sex, head of household's sex, place of residence, state, household owning radio and television, number of household members, wealth quintile, years since ITN was obtained and level of malaria endemicity. Multi-level logistic regression model was used to access factors associated with ITN use among children.ResultsIn total, 32,087 CU5 and 54,692 children of school age were examined with 74.3% of CU5 and 57.8% of children of school age using ITN the night before the survey. While seven states had more than 80% of CU5 who used ITN, only one state had over 80% of school children who used ITN. ITN use in CU5 is associated with living in rural area (aOR = 1.20, 95% CI 1.14 to 1.26) and residing in meso endemic area (aOR = 3.1, 95% CI 2.89 to 3.54). While In children of school age, use of ITN was associated with female headed households (aOR = 1.14, 95% CI 1.09 to 1.19), meso (aOR = 3.17, 95% CI 2.89 to 3.47) and hyper (aOR = 14.9, 95% CI 12.99 to 17.07) endemic areas. Children residing in larger households were less likely to use ITN.ConclusionsThis study demonstrated increased use of ITN in CU5 from poor households and children living in rural and malaria endemic areas. Findings provide some policy recommendations for increasing ITN use in school children.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Use of insecticide treated nets (ITN), one of the most cost-effective malaria interventions contributes to malaria cases averted and reduction in child mortality. We explored the use of ITN in ...children under five (CU5) and children of school age to understand factors contributing to ITN use. A cross-sectional study analyzed 2018 Nigeria Demographic and Health Survey data. The outcome variable was CU5 or children of school age who slept under ITN the night before the survey. Independent variables include child sex, head of household's sex, place of residence, state, household owning radio and television, number of household members, wealth quintile, years since ITN was obtained and level of malaria endemicity. Multi-level logistic regression model was used to access factors associated with ITN use among children. In total, 32,087 CU5 and 54,692 children of school age were examined with 74.3% of CU5 and 57.8% of children of school age using ITN the night before the survey. While seven states had more than 80% of CU5 who used ITN, only one state had over 80% of school children who used ITN. ITN use in CU5 is associated with living in rural area (aOR = 1.20, 95% CI 1.14 to 1.26) and residing in meso endemic area (aOR = 3.1, 95% CI 2.89 to 3.54). While In children of school age, use of ITN was associated with female headed households (aOR = 1.14, 95% CI 1.09 to 1.19), meso (aOR = 3.17, 95% CI 2.89 to 3.47) and hyper (aOR = 14.9, 95% CI 12.99 to 17.07) endemic areas. Children residing in larger households were less likely to use ITN. This study demonstrated increased use of ITN in CU5 from poor households and children living in rural and malaria endemic areas. Findings provide some policy recommendations for increasing ITN use in school children.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Although Nigeria has made some progress in malaria control, there are variations across States. We investigated the factors associated with utilisation of long-lasting insecticide-treated net (LLIN) ...and parasitaemia among under-five children in 13 States with high malaria burden.
Data from the 2015 Nigeria Malaria Indicator Survey and 2018 Demographic and Health Survey were obtained and analysed. The 2015 and 2018 data were compared to identify States with increase or reduction in parasitaemia. Analysis was done for all the 13 study States; four States with increased parasitaemia and nine States with reduction. Random-effects logit models were fitted to identify independent predictors of LLIN utilisation and parasitaemia.
LLIN was used by 53.4% of 2844 children, while parasitaemia prevalence was 26.4% in 2018. Grandchildren (AOR = 5.35, CI: 1.09-26.19) were more likely to use LLIN while other relatives (AOR = 0.33, CI: 0.11-0.94) were less likely compared to children of household-heads. LLIN use was more common in children whose mother opined that only weak children could die from malaria (AOR = 1.83, CI: 1.10-3.10). Children whose mothers obtained net from antenatal or immunisation clinics (AOR = 5.30, CI: 2.32-12.14) and campaigns (AOR = 1.77, CI: 1.03-3.04) were also more likely to use LLIN. In contrast, LLIN utilisation was less likely among children in female-headed households (AOR = 0.51, CI: 0.27-0.99) and those in poor-quality houses (AOR = 0.25, CI: 0.09-0.72). Children aged 24-59 months compared to 0-11 months (AOR = 1.78, CI: 1.28-2.48), those in whom fever was reported (AOR = 1.31, CI: 1.06-1.63) and children of uneducated women (AOR = 1.89, CI: 1.32-2.70) were more likely to have parasitaemia. The likelihood of parasitaemia was higher among children from poor households compared to the rich (AOR = 2.06, CI: 1.24-3.42). The odds of parasitaemia were 98% higher among rural children (AOR = 1.98, CI: 1.37-2.87).
The key drivers of LLIN utilisation were source of net and socioeconomic characteristics. The latter was also a key factor associated with parasitaemia. These should be targeted as part of integrated malaria elimination efforts.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With global progress towards malaria reduction stalling, further analysis of epidemiology is required, particularly in countries with the highest burden. National surveys have mostly analysed ...infection prevalence, while large-scale data on parasite density and different developmental forms rarely available. In Nigeria, the country with the largest burden globally, blood slide microscopy of children up to 5 years of age was conducted in the 2018 National Demographic and Health Survey, and parasite prevalence previously reported. In the current study, malaria parasite density measurements are reported and analysed for 7783 of the children sampled across the 36 states within the six geopolitical zones of the country. Asexual and sexual stages, and infections with different malaria parasite species are analysed. Across all states of Nigeria, there was a positive correlation between mean asexual parasite density within infected individuals and prevalence of infection in the community (Spearman's rho = 0.39, P = 0.02). Asexual parasite densities were highest in the northern geopolitical zones (geometric means > 2000 μL
), extending the evidence of exceptionally high infection burden in many areas. Sexual parasite prevalence in each state was highly correlated with asexual parasite prevalence (Spearman's rho = 0.70, P < 0.001), although sexual parasite densities were low (geometric means < 100 μL
in all zones). Infants had lower parasite densities than children above 1 year of age, but there were no differences between male and female children. Most infections were of P. falciparum, which had higher asexual densities but lower sexual parasite densities than P. malariae or P. ovale mono-infections. However, mixed species infections had the highest asexual parasite densities. It is recommended that future large surveys in high burden countries measure parasite densities as well as developmental stages and species, to improve the quality of malaria epidemiology and tracking of future changes.
SMC was adopted in Nigeria in 2014 and by 2021 was being implemented in 18 states, over four months between June and October by 143000 community drug distributors (CDDs) to a target population of ...23million children. Further expansion of SMC is planned, extending to 21 states with four or five monthly cycles. In view of this massive scale-up, the National Malaria Elimination Programme undertook qualitative research in five states shortly after the 2021 campaign to understand community attitudes to SMC so that these perspectives inform future planning of SMC delivery in Nigeria.
In 20 wards representing urban and rural areas with low and high SMC coverage in five states, focus group discussions were held with caregivers, and in-depth interviews conducted with community leaders and community drug distributors. Interviews were also held with local government area and State malaria focal persons and at national level with the NMEP coordinator, and representatives of partners working on SMC in Nigeria. Interviews were recorded and transcribed, those in local languages translated into English, and transcripts analysed using NVivo software.
In total, 84 focus groups and 106 interviews were completed. Malaria was seen as a major health concern, SMC was widely accepted as a key preventive measure, and community drug distributors (CDDs) were generally trusted. Caregivers preferred SMC delivered door-to-door to the fixed-point approach, because it allowed them to continue daily tasks, and allowed time for the CDD to answer questions. Barriers to SMC uptake included perceived side-effects of SMC drugs, a lack of understanding of the purpose of SMC, mistrust and suspicions that medicines provided free may be unsafe or ineffective, and local shortages of drugs.
Recommendations from this study were shared with all community drug distributors and others involved in SMC campaigns during cascade training in 2022, including the need to strengthen communication about the safety and effectiveness of SMC, recruiting distributors from the local community, greater involvement of state and national level pharmacovigilance coordinators, and stricter adherence to the planned medicine allocations to avoid local shortages. The findings reinforce the importance of retaining door-to-door delivery of SMC.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The neglected tropical diseases (NTDs) affect hundreds of millions of people, predominantly in rural, often difficult-to-access areas, poorly served by national health services. Here, we review the ...contributions of 4.8 million community-directed distributors (CDDs) of medicines over 2 decades in 146,000 communities in 27 sub-Saharan African countries to control or eliminate onchocerciasis and lymphatic filariasis (LF). We examine their role in the control of other NTDs, malaria, HIV/AIDS interventions, immunisation campaigns, and support to overstretched health service personnel. We are of the opinion that CDDs as community selected, trained, and experienced "foot soldiers," some of whom were involved in the Ebola outbreak responses at the community level in Liberia, if retrained, can assist community leaders and support health workers (HWs) in the ongoing Coronavirus Disease 2019 (COVID-19) crisis. The review highlights the improved treatment coverage where there are women CDDs, the benefits and lessons from the work of CDDs, their long-term engagement, and the challenges they face in healthcare delivery. It underscores the value of utilising the CDD model for strong community engagement and recommends the model, with some review, to hasten the achievement of the NTD 2030 goal and assist the health system cope with evolving epidemics and other challenges. We propose that, based on the unprecedented progress made in the control of NTDs directly linked to community engagement and contributions of CDDs "foot soldiers," they deserve regional and global recognition. We also suggest that the World Health Organization (WHO) and other international stakeholders promote policy and guidance for countries to adapt this model for the elimination of NTDs and to strengthen national health services. This will enhance the accomplishment of some Sustainable Development Goals (SDGs) by 2030 in sub-Saharan Africa.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Rapid urbanization in Nigerian cities may lead to localized variations in malaria transmission, particularly with a higher burden in informal settlements and slums. However, there ...is a lack of available data to quantify the variations in transmission risk at the city level and inform the selection of appropriate interventions. To bridge this gap, field studies will be undertaken in Ibadan and Kano, two major Nigerian cities. These studies will involve a blend of cross-sectional and longitudinal epidemiological research, coupled with longitudinal entomological studies. The primary objective is to gain insights into the variation of malaria risk at the smallest administrative units, known as wards, within these cities.
Methods/results
The findings will contribute to the tailoring of interventions as part of Nigeria’s National Malaria Strategic Plan. The study design incorporates a combination of model-based clustering and on-site visits for ground-truthing, enabling the identification of environmental archetypes at the ward-level to establish the study’s framework. Furthermore, community participatory approaches will be utilized to refine study instruments and sampling strategies. The data gathered through cross-sectional and longitudinal studies will contribute to an enhanced understanding of malaria risk in the metropolises of Kano and Ibadan.
Conclusions
This paper outlines pioneering field study methods aimed at collecting data to inform the tailoring of malaria interventions in urban settings. The integration of multiple study types will provide valuable data for mapping malaria risk and comprehending the underlying determinants. Given the importance of location-specific data for microstratification, this study presents a systematic process and provides adaptable tools that can be employed in cities with limited data availability
.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The baseline endemicity profile of lymphatic filariasis (LF) is a key benchmark for planning control programmes, monitoring their impact on transmission and assessing the feasibility of achieving ...elimination. Presented in this work is the modelled serological and parasitological prevalence of LF prior to the scale-up of mass drug administration (MDA) in Nigeria using a machine learning based approach.
LF prevalence data generated by the Nigeria Lymphatic Filariasis Control Programme during country-wide mapping surveys conducted between 2000 and 2013 were used to build the models. The dataset comprised of 1103 community-level surveys based on the detection of filarial antigenemia using rapid immunochromatographic card tests (ICT) and 184 prevalence surveys testing for the presence of microfilaria (Mf) in blood. Using a suite of climate and environmental continuous gridded variables and compiled site-level prevalence data, a quantile regression forest (QRF) model was fitted for both antigenemia and microfilaraemia LF prevalence. Model predictions were projected across a continuous 5 × 5 km gridded map of Nigeria. The number of individuals potentially infected by LF prior to MDA interventions was subsequently estimated.
Maps presented predict a heterogeneous distribution of LF antigenemia and microfilaraemia in Nigeria. The North-Central, North-West, and South-East regions displayed the highest predicted LF seroprevalence, whereas predicted Mf prevalence was highest in the southern regions. Overall, 8.7 million and 3.3 million infections were predicted for ICT and Mf, respectively.
QRF is a machine learning-based algorithm capable of handling high-dimensional data and fitting complex relationships between response and predictor variables. Our models provide a benchmark through which the progress of ongoing LF control efforts can be monitored.
Lymphatic filariasis (LF) is a mosquito-borne parasitic disease and a major cause of disability worldwide. It is one of the neglected tropical diseases identified by the World Health Organization for ...elimination as a public health problem by 2020. Maps displaying disease distribution are helpful tools to identify high-risk areas and target scarce control resources.
We used pre-intervention site-level occurrence data from 1192 survey sites collected during extensive mapping surveys by the Nigeria Ministry of Health. Using an ensemble of machine learning modelling algorithms (generalised boosted models and random forest), we mapped the ecological niche of LF at a spatial resolution of 1 km
. By overlaying gridded estimates of population density, we estimated the human population living in LF risk areas on a 100 × 100 m scale.
Our maps demonstrate that there is a heterogeneous distribution of LF risk areas across Nigeria, with large portions of northern Nigeria having more environmentally suitable conditions for the occurrence of LF. Here we estimated that approximately 110 million individuals live in areas at risk of LF transmission.
Machine learning and ensemble modelling are powerful tools to map disease risk and are known to yield more accurate predictive models with less uncertainty than single models. The resulting map provides a geographical framework to target control efforts and assess its potential impacts.
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