Drivers of long-lasting insecticide-treated net utilisation and parasitaemia among under-five children in 13 States with high malaria burden in Nigeria

BACKGROUND: 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. METHOD: 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. RESULTS: 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). CONCLUSION: 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

Non-falciparum malaria infection and IgG seroprevalence among children under 15 years in Nigeria, 2018.

Plasmodium falciparum (Pf) is the dominant malaria parasite in Nigeria though P. vivax (Pv), P. ovale (Po), and P. malariae (Pm) are also endemic. Blood samples (n = 31,234) were collected from children aged 0-14 years during a 2018 nationwide HIV survey and assayed for Plasmodium antigenemia, Plasmodium DNA, and IgG against Plasmodium MSP1-19 antigens. Of all children, 6.6% were estimated to have Pm infection and 1.4% Po infection with no Pv infections detected. The highest household wealth quintile was strongly protective against infection with Pm (aOR: 0.11, 95% CI: 0.05-0.22) or Po (aOR= 0.01, 0.00-0.10). Overall Pm seroprevalence was 34.2% (95% CI: 33.3-35.2) with lower estimates for Po (12.1%, 11.6-12.5) and Pv (6.3%, 6.0-6.7). Pm seropositivity was detected throughout the country with several local government areas showing >50% seroprevalence. Serological and DNA indicators show widespread exposure of Nigerian children to Pm with lower rates to Po and Pv

Application of mathematical modelling to inform national malaria intervention planning in Nigeria

Background For their 2021–2025 National Malaria Strategic Plan (NMSP), Nigeria’s National Malaria Elimination Programme (NMEP), in partnership with the World Health Organization (WHO), developed a targeted approach to intervention deployment at the local government area (LGA) level as part of the High Burden to High Impact response. Mathematical models of malaria transmission were used to predict the impact of proposed intervention strategies on malaria burden. Methods An agent-based model of Plasmodium falciparum transmission was used to simulate malaria morbidity and mortality in Nigeria’s 774 LGAs under four possible intervention strategies from 2020 to 2030. The scenarios represented the previously implemented plan (business-as-usual), the NMSP at an 80% or higher coverage level and two prioritized plans according to the resources available to Nigeria. LGAs were clustered into 22 epidemiological archetypes using monthly rainfall, temperature suitability index, vector abundance, pre-2010 parasite prevalence, and pre-2010 vector control coverage. Routine incidence data were used to parameterize seasonality in each archetype. Each LGA’s baseline malaria transmission intensity was calibrated to parasite prevalence in children under the age of five years measured in the 2010 Malaria Indicator Survey (MIS). Intervention coverage in the 2010–2019 period was obtained from the Demographic and Health Survey, MIS, the NMEP, and post-campaign surveys. Results Pursuing a business-as-usual strategy was projected to result in a 5% and 9% increase in malaria incidence in 2025 and 2030 compared with 2020, while deaths were projected to remain unchanged by 2030. The greatest intervention impact was associated with the NMSP scenario with 80% or greater coverage of standard interventions coupled with intermittent preventive treatment in infants and extension of seasonal malaria chemoprevention (SMC) to 404 LGAs, compared to 80 LGAs in 2019. The budget-prioritized scenario with SMC expansion to 310 LGAs, high bed net coverage with new formulations, and increase in effective case management rate at the same pace as historical levels was adopted as an adequate alternative for the resources available. Conclusions Dynamical models can be applied for relative assessment of the impact of intervention scenarios but improved subnational data collection systems are required to allow increased confidence in predictions at sub-national level

Design and methods for a quasi-experimental pilot study to evaluate the impact of dual active ingredient insecticide-treated nets on malaria burden in five regions in sub-Saharan Africa

Background Vector control tools have contributed significantly to a reduction in malaria burden since 2000, primarily through insecticidal-treated bed nets (ITNs) and indoor residual spraying. In the face of increasing insecticide resistance in key malaria vector species, global progress in malaria control has stalled. Innovative tools, such as dual active ingredient (dual-AI) ITNs that are effective at killing insecticide-resistant mosquitoes have recently been introduced. However, large-scale uptake has been slow for several reasons, including higher costs and limited evidence on their incremental effectiveness and cost-effectiveness. The present report describes the design of several observational studies aimed to determine the effectiveness and cost-effectiveness of dual-AI ITNs, compared to standard pyrethroid-only ITNs, at reducing malaria transmission across a variety of transmission settings. Methods Observational pilot studies are ongoing in Burkina Faso, Mozambique, Nigeria, and Rwanda, leveraging dual-AI ITN rollouts nested within the 2019 and 2020 mass distribution campaigns in each country. Enhanced surveillance occurring in select study districts include annual cross-sectional surveys during peak transmission seasons, monthly entomological surveillance, passive case detection using routine health facility surveillance systems, and studies on human behaviour and ITN use patterns. Data will compare changes in malaria transmission and disease burden in districts receiving dual-AI ITNs to similar districts receiving standard pyrethroid-only ITNs over three years. The costs of net distribution will be calculated using the provider perspective including financial and economic costs, and a cost-effectiveness analysis will assess incremental cost-effectiveness ratios for Interceptor® G2, Royal Guard®, and piperonyl butoxide ITNs in comparison to standard pyrethroid-only ITNs, based on incidence rate ratios calculated from routine data. Conclusions Evidence of the effectiveness and cost-effectiveness of the dual-AI ITNs from these pilot studies will complement evidence from two contemporary cluster randomized control trials, one in Benin and one in Tanzania, to provide key information to malaria control programmes, policymakers, and donors to help guide decision-making and planning for local malaria control and elimination strategies. Understanding the breadth of contexts where these dual-AI ITNs are most effective and collecting robust information on factors influencing comparative effectiveness could improve uptake and availability and help maximize their impact

The potential public health consequences of COVID-19 on malaria in Africa.

The burden of malaria is heavily concentrated in sub-Saharan Africa (SSA) where cases and deaths associated with COVID-19 are rising1. In response, countries are implementing societal measures aimed at curtailing transmission of SARS-CoV-22,3. Despite these measures, the COVID-19 epidemic could still result in millions of deaths as local health facilities become overwhelmed4. Advances in malaria control this century have been largely due to distribution of long-lasting insecticidal nets (LLINs)5, with many SSA countries having planned campaigns for 2020. In the present study, we use COVID-19 and malaria transmission models to estimate the impact of disruption of malaria prevention activities and other core health services under four different COVID-19 epidemic scenarios. If activities are halted, the malaria burden in 2020 could be more than double that of 2019. In Nigeria alone, reducing case management for 6 months and delaying LLIN campaigns could result in 81,000 (44,000-119,000) additional deaths. Mitigating these negative impacts is achievable, and LLIN distributions in particular should be prioritized alongside access to antimalarial treatments to prevent substantial malaria epidemics