Incremental cost and cost-effectiveness of the addition of indoor residual spraying with pirimiphos-methyl in sub-Saharan Africa versus standard malaria control: results of data collection and analysis in the Next Generation Indoor Residual Sprays (NgenIRS) project, an economic-evaluation.

BACKGROUND: Malaria is a major cause of morbidity and mortality globally, especially in sub-Saharan Africa. Widespread resistance to pyrethroids threatens the gains achieved by vector control. To counter resistance to pyrethroids, third-generation indoor residual spraying (3GIRS) products have been developed. This study details the results of a multi-country cost and cost-effectiveness analysis of indoor residual spraying (IRS) programmes using Actellic®300CS, a 3GIRS product with pirimiphos-methyl, in sub-Saharan Africa in 2017 added to standard malaria control interventions including insecticide-treated bed nets versus standard malaria control interventions alone. METHODS: An economic evaluation of 3GIRS using Actellic®300CS in a broad range of sub-Saharan African settings was conducted using a variety of primary data collection and evidence synthesis methods. Four IRS programmes in Ghana, Mali, Uganda, and Zambia were included in the effectiveness analysis. Cost data come from six IRS programmes: one in each of the four countries where effect was measured plus Mozambique and a separate programme conducted by AngloGold Ashanti Malaria Control in Ghana. Financial and economic costs were quantified and valued. The main indicator for the cost was cost per person targeted. Country-specific case incidence rate ratios (IRRs), estimated by comparing IRS study districts to adjacent non-IRS study districts or facilities, were used to calculate cases averted in each study area. A deterministic analysis and sensitivity analysis were conducted in each of the four countries for which effectiveness evaluations were available. Probabilistic sensitivity analysis was used to generate plausibility bounds around the incremental cost-effectiveness ratio estimates for adding IRS to other standard interventions in each study setting as well as jointly utilizing data on effect and cost across all settings. RESULTS: Overall, IRRs from each country indicated that adding IRS with Actellic®300CS to the local standard intervention package was protective compared to the standard intervention package alone (IRR 0.67, [95% CI 0.50-0.91]). Results indicate that Actellic®300CS is expected to be a cost-effective (> 60% probability of being cost-effective in all settings) or highly cost-effective intervention across a range of transmission settings in sub-Saharan Africa. DISCUSSION: Variations in the incremental costs and cost-effectiveness likely result from several sources including: variation in the sprayed wall surfaces and house size relative to household population, the underlying malaria burden in the communities sprayed, the effectiveness of 3GIRS in different settings, and insecticide price. Programmes should be aware that current recommendations to rotate can mean variation and uncertainty in budgets; programmes should consider this in their insecticide-resistance management strategies. CONCLUSIONS: The optimal combination of 3GIRS delivery with other malaria control interventions will be highly context specific. 3GIRS using Actellic®300CS is expected to deliver acceptable value for money in a broad range of sub-Saharan African malaria transmission settings.

Rapid shifts in the age-specific burden of malaria following successful control interventions in four regions of Uganda.

BACKGROUND: Malaria control using long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) has been associated with reduced transmission throughout Africa. However, the impact of transmission reduction on the age distribution of malaria cases remains unclear. METHODS: Over a 10-year period (January 2009 to July 2018), outpatient surveillance data from four health facilities in Uganda were used to estimate the impact of control interventions on temporal changes in the age distribution of malaria cases using multinomial regression. Interventions included mass distribution of LLINs at all sites and IRS at two sites. RESULTS: Overall, 896,550 patient visits were included in the study; 211,632 aged < 5 years, 171,166 aged 5-15 years and 513,752 > 15 years. Over time, the age distribution of patients not suspected of malaria and those malaria negative either declined or remained the same across all sites. In contrast, the age distribution of suspected and confirmed malaria cases increased across all four sites. In the two LLINs-only sites, the proportion of malaria cases in < 5 years decreased from 31 to 16% and 35 to 25%, respectively. In the two sites receiving LLINs plus IRS, these proportions decreased from 58 to 30% and 64 to 47%, respectively. Similarly, in the LLINs-only sites, the proportion of malaria cases > 15 years increased from 40 to 61% and 29 to 39%, respectively. In the sites receiving LLINs plus IRS, these proportions increased from 19 to 44% and 18 to 31%, respectively. CONCLUSIONS: These findings demonstrate a shift in the burden of malaria from younger to older individuals following implementation of successful control interventions, which has important implications for malaria prevention, surveillance, case management and control strategies.

The effect of case management and vector-control interventions on space-time patterns of malaria incidence in Uganda.

BACKGROUND: Electronic reporting of routine health facility data in Uganda began with the adoption of the District Health Information Software System version 2 (DHIS2) in 2011. This has improved health facility reporting and overall data quality. In this study, the effects of case management with artemisinin-based combination therapy (ACT) and vector control interventions on space-time patterns of disease incidence were determined using DHIS2 data reported during 2013-2016. METHODS: Bayesian spatio-temporal negative binomial models were fitted on district-aggregated monthly malaria cases, reported by two age groups, defined by a cut-off age of 5 years. The effects of interventions were adjusted for socio-economic and climatic factors. Spatial and temporal correlations were taken into account by assuming a conditional autoregressive and a first-order autoregressive AR(1) process on district and monthly specific random effects, respectively. Fourier trigonometric functions were incorporated in the models to take into account seasonal fluctuations in malaria transmission. RESULTS: The temporal variation in incidence was similar in both age groups and depicted a steady decline up to February 2014, followed by an increase from March 2015 onwards. The trends were characterized by a strong bi-annual seasonal pattern with two peaks during May-July and September-December. Average monthly incidence in children < 5 years declined from 74.7 cases (95% CI 72.4-77.1) in 2013 to 49.4 (95% CI 42.9-55.8) per 1000 in 2015 and followed by an increase in 2016 of up to 51.3 (95% CI 42.9-55.8). In individuals ≥ 5 years, a decline in incidence from 2013 to 2015 was followed by an increase in 2016. A 100% increase in insecticide-treated nets (ITN) coverage was associated with a decline in incidence by 44% (95% BCI 28-59%). Similarly, a 100% increase in ACT coverage reduces incidence by 28% (95% BCI 11-45%) and 25% (95% BCI 20-28%) in children < 5 years and individuals ≥ 5 years, respectively. The ITN effect was not statistically important in older individuals. The space-time patterns of malaria incidence in children < 5 are similar to those of parasitaemia risk predicted from the malaria indicator survey of 2014-15. CONCLUSION: The decline in malaria incidence highlights the effectiveness of vector-control interventions and case management with ACT in Uganda. This calls for optimizing and sustaining interventions to achieve universal coverage and curb reverses in malaria decline.