0734 Cost-effectiveness analysis of PBO-LLINs compared to Non PBO LLINs in the reduction of malaria among children in Jinja district

abstract appears in Infection Prevention & Control / International Journal of Infectious Diseases 101(S1) (2021) 300–335 the organizers of the 19th International Congress on Infectious Diseases (ICID) made the decision to cancel the Congress scheduled for September 10-13, 2020 in Kuala Lumpur, Malaysi

East Africa International Center of Excellence for Malaria Research: Impact on Malaria Policy in Uganda

Malaria is the leading cause of disease burden in sub-Saharan Africa. In 2010, the East Africa International Center of Excellence for Malaria Research, also known as the Program for Resistance, Immunology, Surveillance, and Modeling of Malaria (PRISM), was established to provide a comprehensive approach to malaria surveillance in Uganda. We instituted cohort studies and a robust malaria and entomological surveillance network at selected public health facilities that have provided a platform for monitoring trends in malaria morbidity and mortality, tracking the impact of malaria control interventions (indoor residual spraying of insecticide [IRS], use of long-lasting insecticidal nets [LLINs], and case management with artemisinin-based combination therapies [ACTs]), as well as monitoring of antimalarial drug and insecticide resistance. PRISM studies have informed Uganda's malaria treatment policies, guided selection of LLINs for national distribution campaigns, and revealed widespread pyrethroid resistance, which led to changes in insecticides delivered through IRS. Our continuous engagement and interaction with policy makers at the Ugandan Ministry of Health have enabled PRISM to share evidence, best practices, and lessons learned with key malaria stakeholders, participate in malaria control program reviews, and contribute to malaria policy and national guidelines. Here, we present an overview of interactions between PRISM team members and Ugandan policy makers to demonstrate how PRISM's research has influenced malaria policy and control in Uganda

Molecular surveillance reveals the presence of pfhrp2 and pfhrp3 gene deletions in Plasmodium falciparum parasite populations in Uganda, 2017–2019

Abstract Background Histidine-rich protein-2 (HRP2)-based rapid diagnostic tests (RDTs) are the only RDTs recommended for malaria diagnosis in Uganda. However, the emergence of Plasmodium falciparum histidine rich protein 2 and 3 (pfhrp2 and pfhrp3) gene deletions threatens their usefulness as malaria diagnostic and surveillance tools. The pfhrp2 and pfhrp3 gene deletions surveillance was conducted in P. falciparum parasite populations in Uganda. Methods Three-hundred (n = 300) P. falciparum isolates collected from cross-sectional malaria surveys in symptomatic individuals in 48 districts of eastern and western Uganda were analysed for the presence of pfhrp2 and pfhrp3 genes. Presence of parasite DNA was confirmed by PCR amplification of the 18s rRNA gene, msp1 and msp2 single copy genes. Presence or absence of deletions was confirmed by amplification of exon1 and exon2 of pfhrp2 and pfhrp3 using gene specific PCR. Results Overall, pfhrp2 and pfhrp3 gene deletions were detected in 29/300 (9.7%, 95% CI 6.6–13.6%) parasite isolates. The pfhrp2 gene was deleted in 10/300 (3.3%, 95% CI 1.6–6.0%) isolates, pfhrp3 in 9/300 (3.0%, 95% CI 1.4–5.6%) while both pfhrp2 and pfhrp3 were deleted in 10/300 (3.3%, 95% CI 1.6–6.0%) parasite isolates. Proportion of pfhrp2/3 deletions was higher in the eastern 14.7% (95% CI 9.7–20.0%) compared to the western region 3.1% (95% CI 0.8–7.7%), p = 0.001. Geographical location was associated with gene deletions aOR 6.25 (2.02–23.55), p = 0.003. Conclusions This is the first large-scale survey reporting the presence of pfhrp2/3 gene deletions in P. falciparum isolates in Uganda. Roll out of RDTs for malaria diagnosis should take into consideration the existence of pfhrp2/3 gene deletions particularly in areas where they were detected. Periodic pfhrp2/3 surveys are recommended to inform future decisions for deployment of alternative RDTs

Optimising the deployment of vector control tools against malaria: a data-informed modelling study

Background Concern that insecticide resistant mosquitoes are threatening malaria control has driven the development of new types of insecticide treated nets (ITNs) and indoor residual spraying (IRS) of insecticide. Malaria control programmes have a choice of vector control interventions although it is unclear which controls should be used to combat the disease. The study aimed at producing a framework to easily compare the public health impact and cost-effectiveness of different malaria prevention measures currently in widespread use. Methods We used published data from experimental hut trials conducted across Africa to characterise the entomological effect of pyrethroid-only ITNs versus ITNs combining a pyrethroid insecticide with the synergist piperonyl butoxide (PBO). We use these estimates to parameterise a dynamic mathematical model of Plasmodium falciparum malaria which is validated for two sites by comparing simulated results to empirical data from randomised control trials (RCTs) in Tanzania and Uganda. We extrapolated model simulations for a series of potential scenarios likely across the sub-Saharan African region and include results in an online tool (Malaria INtervention Tool [MINT]) that aims to identify optimum vector control intervention packages for scenarios with varying budget, price, entomological and epidemiological factors. Findings Our model indicates that switching from pyrethroid-only to pyrethroid-PBO ITNs could averted up to twice as many cases, although the additional benefit is highly variable and depends on the setting conditions. We project that annual delivery of long-lasting, non-pyrethroid IRS would prevent substantially more cases over 3-years, while pyrethroid-PBO ITNs tend to be the most cost-effective intervention per case averted. The model was able to predict prevalence and efficacy against prevalence in both RCTs for the intervention types tested. MINT is applicable to regions of sub-Saharan Africa with endemic malaria and provides users with a method of designing intervention packages given their setting and budget. Interpretation The most cost-effective vector control package will vary locally. Models able to recreate results of RCTs can be used to extrapolate outcomes elsewhere to support evidence-based decision making for investment in vector control

Uganda's experience in Ebola virus disease outbreak preparedness, 2018-2019.

BACKGROUND: Since the declaration of the 10th Ebola Virus Disease (EVD) outbreak in DRC on 1st Aug 2018, several neighboring countries have been developing and implementing preparedness efforts to prevent EVD cross-border transmission to enable timely detection, investigation, and response in the event of a confirmed EVD outbreak in the country. We describe Uganda's experience in EVD preparedness. RESULTS: On 4 August 2018, the Uganda Ministry of Health (MoH) activated the Public Health Emergency Operations Centre (PHEOC) and the National Task Force (NTF) for public health emergencies to plan, guide, and coordinate EVD preparedness in the country. The NTF selected an Incident Management Team (IMT), constituting a National Rapid Response Team (NRRT) that supported activation of the District Task Forces (DTFs) and District Rapid Response Teams (DRRTs) that jointly assessed levels of preparedness in 30 designated high-risk districts representing category 1 (20 districts) and category 2 (10 districts). The MoH, with technical guidance from the World Health Organisation (WHO), led EVD preparedness activities and worked together with other ministries and partner organisations to enhance community-based surveillance systems, develop and disseminate risk communication messages, engage communities, reinforce EVD screening and infection prevention measures at Points of Entry (PoEs) and in high-risk health facilities, construct and equip EVD isolation and treatment units, and establish coordination and procurement mechanisms. CONCLUSION: As of 31 May 2019, there was no confirmed case of EVD as Uganda has continued to make significant and verifiable progress in EVD preparedness. There is a need to sustain these efforts, not only in EVD preparedness but also across the entire spectrum of a multi-hazard framework. These efforts strengthen country capacity and compel the country to avail resources for preparedness and management of incidents at the source while effectively cutting costs of using a "fire-fighting" approach during public health emergencies

Plasmodium falciparum parasite prevalence in East Africa: Updating data for malaria stratification

The High Burden High Impact (HBHI) strategy for malaria encourages countries to use multiple sources of available data to define the sub-national vulnerabilities to malaria risk, including parasite prevalence. Here, a modelled estimate of Plasmodium falciparum from an updated assembly of community parasite survey data in Kenya, mainland Tanzania, and Uganda is presented and used to provide a more contemporary understanding of the sub-national malaria prevalence stratification across the sub-region for 2019. Malaria prevalence data from surveys undertaken between January 2010 and June 2020 were assembled form each of the three countries. Bayesian spatiotemporal model-based approaches were used to interpolate space-time data at fine spatial resolution adjusting for population, environmental and ecological covariates across the three countries. A total of 18,940 time-space age-standardised and microscopy-converted surveys were assembled of which 14,170 (74.8%) were identified after 2017. The estimated national population-adjusted posterior mean parasite prevalence was 4.7% (95% Bayesian Credible Interval 2.6–36.9) in Kenya, 10.6% (3.4–39.2) in mainland Tanzania, and 9.5% (4.0–48.3) in Uganda. In 2019, more than 12.7 million people resided in communities where parasite prevalence was predicted ≥ 30%, including 6.4%, 12.1% and 6.3% of Kenya, mainland Tanzania and Uganda populations, respectively. Conversely, areas that supported very low parasite prevalence (<1%) were inhabited by approximately 46.2 million people across the sub-region, or 52.2%, 26.7% and 10.4% of Kenya, mainland Tanzania and Uganda populations, respectively. In conclusion, parasite prevalence represents one of several data metrics for disease stratification at national and sub-national levels. To increase the use of this metric for decision making, there is a need to integrate other data layers on mortality related to malaria, malaria vector composition, insecticide resistance and bionomic, malaria care-seeking behaviour and current levels of unmet need of malaria interventions

LLIN Evaluation in Uganda Project (LLINEUP): modelling the impact of COVID-19-related disruptions on delivery of long-lasting insecticidal nets on malaria indicators in Uganda

Background: Disruptions in malaria control due to COVID-19 mitigation measures were predicted to increase malaria morbidity and mortality in Africa substantially. In Uganda, long-lasting insecticidal nets (LLINs) are distributed nationwide every 3–4 years, but the 2020–2021 campaign was altered because of COVID-19 restrictions so that the timing of delivery of new nets was different from the original plans made by the National Malaria Control Programme. Methods: A transmission dynamics modelling exercise was conducted to explore how the altered delivery of LLINs in 2020–2021 impacted malaria burden in Uganda. Data were available on the planned LLIN distribution schedule for 2020–2021, and the actual delivery. The transmission model was used to simulate 100 health sub-districts, and parameterized to match understanding of local mosquito bionomics, net use estimates, and seasonal patterns based on data collected in 2017–2019 during a cluster-randomized trial (LLINEUP). Two scenarios were compared; simulated LLIN distributions matching the actual delivery schedule, and a comparable scenario simulating LLIN distributions as originally planned. Model parameters were otherwise matched between simulations. Results: Approximately 70% of the study population received LLINs later than scheduled in 2020–2021, although some areas received LLINs earlier than planned. The model indicates that malaria incidence in 2020 was substantially higher in areas that received LLINs late. In some areas, early distribution of LLINs appeared less effective than the original distribution schedule, possibly due to attrition of LLINs prior to transmission peaks, and waning LLIN efficacy after distribution. On average, the model simulations predicted broadly similar overall mean malaria incidence in 2021 and 2022. After accounting for differences in cluster population size and LLIN distribution dates, no substantial increase in malaria burden was detected. Conclusions: The model results suggest that the disruptions in the 2020–2021 LLIN distribution campaign in Uganda did not substantially increase malaria burden in the study areas

Inferring the epidemiological benefit of indoor vector control interventions against malaria from mosquito data

The cause of malaria transmission has been known for over a century but it is still unclear whether entomological measures are sufficiently reliable to inform policy decisions in human health. Decision- making on the effectiveness of new insecticide treated nets (ITNs) and the indoor residual spraying of insecticide (IRS) have been based on epidemiological data, typically collected in cluster-randomised control trials. The number of these trials that can be conducted is limited. Here we use a systematic review to highlight that efficacy estimates of the same intervention may vary substantially between trials. Analyses indicates that mosquito data collected in experimental hut trials can be used to parameterize mechanistic models for Plasmodium falciparum malaria and reliably predict the epidemiological efficacy of quick-acting, neuro-acting ITNs and IRS. Results suggests that for certain types of ITNs and IRS using this framework instead of clinical endpoints could support policy and expedite the widespread use of novel technologies

Inferring the epidemiological benefit of indoor vector control interventions against malaria from mosquito data.

The cause of malaria transmission has been known for over a century but it is still unclear whether entomological measures are sufficiently reliable to inform policy decisions in human health. Decision-making on the effectiveness of new insecticide-treated nets (ITNs) and the indoor residual spraying of insecticide (IRS) have been based on epidemiological data, typically collected in cluster-randomised control trials. The number of these trials that can be conducted is limited. Here we use a systematic review to highlight that efficacy estimates of the same intervention may vary substantially between trials. Analyses indicate that mosquito data collected in experimental hut trials can be used to parameterize mechanistic models for Plasmodium falciparum malaria and reliably predict the epidemiological efficacy of quick-acting, neuro-acting ITNs and IRS. Results suggest that for certain types of ITNs and IRS using this framework instead of clinical endpoints could support policy and expedite the widespread use of novel technologies

Optimising the deployment of vector control tools against malaria: a data-informed modelling study

Background Concern that insecticide resistant mosquitoes are threatening malaria control has driven the development of new types of insecticide treated nets (ITNs) and indoor residual spraying (IRS). Malaria control programmes have a choice of vector control interventions though it is unclear which should be used to combat the disease. Methods The entomological impact of ITNs combining a pyrethroid insecticide with the synergist piperonyl butoxide (PBO) is characterised from experimental hut trials and used to parameterise a malaria transmission dynamics model. Model projections are validated for two sites by comparing results to data from pyrethroid-PBO ITN and IRS randomised control trials (RCTs). Models are used to identify optimum intervention packages for scenarios with varying budget, price, entomological and epidemiological factors. Findings Combining entomological data and models can reasonably predict changes in malaria in the Tanzanian and Ugandan RCTs. Models indicate switching from pyrethroid-only to pyrethroid-PBO ITNs could avert up to twice as many cases, though the additional benefit is highly variable and depends upon setting. Annual delivery of long-lasting, non-pyrethroid IRS is projected to prevent substantially more cases over 3-years, but pyrethroid-PBO ITNs tend to be the most cost-effective intervention per case averted. An online tool (MINT) provides users with a method of designing intervention packages given their setting and budget. Interpretation The most cost-effective vector control package will vary locally. Models able to recreate results of RCTs can be used to extrapolate outcomes elsewhere to support evidence-based decision making for investment in vector control. Funding Medical Research Council, IVCC, Wellcome Trust