Modelling antibody responses to malaria blood stage infections: A novel method to estimate malaria transmission intensity from serological data

Infection with the Plasmodium falciparum malaria parasite results in an immune response which includes the production of antibodies against the blood-stage of infection. In recent years there has been an increase in the use of serological data to monitor malaria transmission intensity. Traditionally, EIR and parasite prevalence were the preferred tools for measuring malaria transmission intensity. Serology has been shown to be particularly useful in areas of low endemicity where traditional measures (EIR and parasite prevalence) are problematic. Transmission intensity in this case is usually described by the seroconversion rate obtained from fitting a catalytic model to age-stratified serological responses. The aim of my thesis was to better utilise the continuous measurements of antibody responses provided by serology studies to obtain improved estimates of transmission intensity. To do this, I developed a series of biologically motivated models to mimic the acquisition and decay in blood-stage antibody responses. In the first part of the thesis, I developed a discrete model as a direct extension of the catalytic model and fitted this to cross-sectional data from several sites in Cambodia to obtain an estimate of the exposure rate. In the second part of the thesis a series of continuous density models were developed to mimic antibody acquisition and loss for P. falciparum infections. These models were fitted to both the Cambodian data and separately validated by fitting to data from Tanzanian villages at a wider range of transmission intensities. In the final section I applied and extended the model to encompass a wider range of endemic transmission in Somalia, Bioko Island, Gambia and Uganda in order to assess the robustness of the method. My results show that estimates of the exposure rate obtained by fitting the density model are highly correlated with classic malariometric indices and that a key advantage of this approach is the increased precision in the estimates compared to estimates of the seroconversion rate, especially in areas of low transmission. This method could therefore be a useful alternative framework for quantifying transmission intensity which makes more complete use of serological data and shows potentials for detecting heterogeneity in malaria exposure.Open Acces

Applied mathematical modelling to inform national malaria policies, strategies and operations in Tanzania

More than ever, it is crucial to make the best use of existing country data, and analytical tools for developing malaria control strategies as the heterogeneity in malaria risk within countries is increasing, and the available malaria control tools are expanding while large funding gaps exist. Global and local policymakers, as well as funders, increasingly recognize the value of mathematical modelling as a strategic tool to support decision making. This case study article describes the long-term use of modelling in close collaboration with the National Malaria Control Programme (NMCP) in Tanzania, the challenges encountered and lessons learned.; In Tanzania, a recent rebound in prevalence led to the revision of the national malaria strategic plan with interventions targeted to the malaria risk at the sub-regional level. As part of the revision, a mathematical malaria modelling framework for setting specific predictions was developed and used between 2016 and 2019 to (1) reproduce setting specific historical malaria trends, and (2) to simulate in silico the impact of future interventions. Throughout the project, multiple stakeholder workshops were attended and the use of mathematical modelling interactively discussed.; In Tanzania, the model application created an interdisciplinary and multisectoral dialogue platform between modellers, NMCP and partners and contributed to the revision of the national malaria strategic plan by simulating strategies suggested by the NMCP. The uptake of the modelling outputs and sustained interest by the NMCP were critically associated with following factors: (1) effective sensitization to the NMCP, (2) regular and intense communication, (3) invitation for the modellers to participate in the strategic plan process, and (4) model application tailored to the local context.; Empirical data analysis and its use for strategic thinking remain the cornerstone for evidence-based decision-making. Mathematical impact modelling can support the process both by unifying all stakeholders in one strategic process and by adding new key evidence required for optimized decision-making. However, without a long-standing partnership, it will be much more challenging to sensibilize programmes to the usefulness and sustained use of modelling and local resources within the programme or collaborating research institutions need to be mobilized

Appropriateness of malaria diagnosis and treatment for fever episodes according to patient history and anti-malarial blood measurement : a cross-sectional survey from Tanzania

Monitoring the impact of case management strategies at large scale is essential to evaluate the public health benefit they confer. The use of methodologies relying on objective and standardized endpoints, such as drug levels in the blood, should be encouraged. Population drug use, diagnosis and treatment appropriateness in case of fever according to patient history and anti-malarials blood concentration was evaluated.; A cross-sectional survey took place between May and August 2015 in three regions of Tanzania with different levels of malaria endemicity. Interviews were conducted and blood samples were collected by dried blood spots through household surveys for further anti-malarial measurements. Appropriate testing when individuals attended care was defined as a patient with history of fever being tested for malaria and appropriate treatment as (i) having anti-malarial in the blood if the test result was positive (ii) having anti-malarial in the blood if the person was not tested, and (iii) no anti-malarial in the blood when the test result was negative.; Amongst 6391 participants included in the anti-malarial analysis, 20.8% (1330/6391) had anti-malarial drug detected in the blood. Only 28.0% (372/1330) of the individuals with anti-malarials in their blood reported the use of anti-malarials within the previous month. Amongst all participants, 16.0% (1021/6391) reported having had a fever in the previous 2 weeks and 37.5% of them (383/1021) had detectable levels of anti-malarials in the blood. Of the individuals who sought care in health facilities, 69.4% (172/248) were tested and 52.0% (129/248) appropriately treated. When other providers were sought, 6% (23/382) of the persons were appropriately tested and 44.2% (169/382) appropriately treated. Overall, the proportion of individuals treated was larger than that being tested [47.3% (298/630) treated, 31.0% (195/630) tested].; This study showed high prevalence of circulating anti-malarial drug in the sampled population. Efforts should be made to increase rapid diagnostic tests use at all levels of health care and improve compliance to test result in order to target febrile patients that are sick with malaria and reduce drug pressure. Objective drug measurements collected at community level represent a reliable tool to evaluate overall impact of case management strategies on population drug pressure

The use of routine health facility data for micro-stratification of malaria risk in mainland Tanzania

Background Current efforts to estimate the spatially diverse malaria burden in malaria-endemic countries largely involve the use of epidemiological modelling methods for describing temporal and spatial heterogeneity using sparse interpolated prevalence data from periodic cross-sectional surveys. However, more malaria-endemic countries are beginning to consider local routine data for this purpose. Nevertheless, routine information from health facilities (HFs) remains widely under-utilized despite improved data quality, including increased access to diagnostic testing and the adoption of the electronic District Health Information System (DHIS2). This paper describes the process undertaken in mainland Tanzania using routine data to develop a high-resolution, micro-stratification risk map to guide future malaria control efforts. Methods Combinations of various routine malariometric indicators collected from 7098 HFs were assembled across 3065 wards of mainland Tanzania for the period 2017–2019. The reported council-level prevalence classification in school children aged 5–16 years (PfPR5–16) was used as a benchmark to define four malaria risk groups. These groups were subsequently used to derive cut-offs for the routine indicators by minimizing misclassifications and maximizing overall agreement. The derived-cutoffs were converted into numbered scores and summed across the three indicators to allocate wards into their overall risk stratum. Results Of 3065 wards, 353 were assigned to the very low strata (10.5% of the total ward population), 717 to the low strata (28.6% of the population), 525 to the moderate strata (16.2% of the population), and 1470 to the high strata (39.8% of the population). The resulting micro-stratification revealed malaria risk heterogeneity within 80 councils and identified wards that would benefit from community-level focal interventions, such as community-case management, indoor residual spraying and larviciding. Conclusion The micro-stratification approach employed is simple and pragmatic, with potential to be easily adopted by the malaria programme in Tanzania. It makes use of available routine data that are rich in spatial resolution and that can be readily accessed allowing for a stratification of malaria risk below the council level. Such a framework is optimal for supporting evidence-based, decentralized malaria control planning, thereby improving the effectiveness and allocation efficiency of malaria control interventions

Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data

Recent malaria control efforts in mainland Tanzania have led to progressive changes in the prevalence of malaria infection in children, from 18.1% (2008) to 7.3% (2017). As the landscape of malaria transmission changes, a sub-national stratification becomes crucial for optimized cost-effective implementation of interventions. This paper describes the processes, data and outputs of the approach used to produce a simplified, pragmatic malaria risk stratification of 184 councils in mainland Tanzania.; Assemblies of annual parasite incidence and fever test positivity rate for the period 2016-2017 as well as confirmed malaria incidence and malaria positivity in pregnant women for the period 2015-2017 were obtained from routine district health information software. In addition, parasite prevalence in school children (PfPR; 5to16; ) were obtained from the two latest biennial council representative school malaria parasitaemia surveys, 2014-2015 and 2017. The PfPR; 5to16; served as a guide to set appropriate cut-offs for the other indicators. For each indicator, the maximum value from the past 3 years was used to allocate councils to one of four risk groups: very low (< 1%PfPR; 5to16; ), low (1- < 5%PfPR; 5to16; ), moderate (5- < 30%PfPR; 5to16; ) and high (≥ 30%PfPR; 5to16; ). Scores were assigned to each risk group per indicator per council and the total score was used to determine the overall risk strata of all councils.; Out of 184 councils, 28 were in the very low stratum (12% of the population), 34 in the low stratum (28% of population), 49 in the moderate stratum (23% of population) and 73 in the high stratum (37% of population). Geographically, most of the councils in the low and very low strata were situated in the central corridor running from the north-east to south-west parts of the country, whilst the areas in the moderate to high strata were situated in the north-west and south-east regions.; A stratification approach based on multiple routine and survey malaria information was developed. This pragmatic approach can be rapidly reproduced without the use of sophisticated statistical methods, hence, lies within the scope of national malaria programmes across Africa

Models of effectiveness of interventions against malaria transmitted by Anopheles albimanus

Most impact prediction of malaria vector control interventions has been based on African vectors. Anopheles albimanus, the main vector in Central America and the Caribbean, has higher intrinsic mortality, is more zoophilic and less likely to rest indoors. Therefore, relative impact among interventions may be different. Prioritizing interventions, in particular for eliminating Plasmodium falciparum from Haiti, should consider local vector characteristics.; Field bionomics data of An. albimanus from Hispaniola and intervention effect data from southern Mexico were used to parameterize mathematical malaria models. Indoor residual spraying (IRS), insecticide-treated nets (ITNs), and house-screening were analysed by inferring their impact on the vectorial capacity in a difference-equation model. Impact of larval source management (LSM) was assumed linear with coverage. Case management, mass drug administration and vaccination were evaluated by estimating their effects on transmission in a susceptible-infected-susceptible model. Analogous analyses were done for Anopheles gambiae parameterized with data from Tanzania, Benin and Nigeria.; While LSM was equally effective against both vectors, impact of ITNs on transmission by An. albimanus was much lower than for An. gambiae. Assuming that people are outside until bedtime, this was similar for the impact of IRS with dichlorodiphenyltrichloroethane (DDT) or bendiocarb, and impact of IRS was less than that of ITNs. However, assuming people go inside when biting starts, IRS had more impact on An. albimanus than ITNs. While house-screening had less impact than ITNs or IRS on An. gambiae, it had more impact on An. albimanus than ITNs or IRS. The impacts of chemoprevention and chemotherapy were comparable in magnitude to those of strategies against An. albimanus. Chemo-prevention impact increased steeply as coverage approached 100%, whilst clinical-case management impact saturated because of remaining asymptomatic infections.; House-screening and repellent IRS are potentially highly effective against An. albimanus if people are indoors during the evening. This is consistent with historical impacts of IRS with DDT, which can be largely attributed to excito-repellency. It also supports the idea that housing improvements have played a critical role in malaria control in North America. For elimination planning, impact estimates need to be combined with feasibility and cost-analysis

Association between the proportion of Plasmodium falciparum and Plasmodium vivax infections detected by passive surveillance and the magnitude of the asymptomatic reservoir in the community: a pooled analysis of paired health facility and community data.

BACKGROUND: Passively collected malaria case data are the foundation for public health decision making. However, because of population-level immunity, infections might not always be sufficiently symptomatic to prompt individuals to seek care. Understanding the proportion of all Plasmodium spp infections expected to be detected by the health system becomes particularly paramount in elimination settings. The aim of this study was to determine the association between the proportion of infections detected and transmission intensity for Plasmodium falciparum and Plasmodium vivax in several global endemic settings. METHODS: The proportion of infections detected in routine malaria data, P(Detect), was derived from paired household cross-sectional survey and routinely collected malaria data within health facilities. P(Detect) was estimated using a Bayesian model in 431 clusters spanning the Americas, Africa, and Asia. The association between P(Detect) and malaria prevalence was assessed using log-linear regression models. Changes in P(Detect) over time were evaluated using data from 13 timepoints over 2 years from The Gambia. FINDINGS: The median estimated P(Detect) across all clusters was 12·5% (IQR 5·3-25·0) for P falciparum and 10·1% (5·0-18·3) for P vivax and decreased as the estimated log-PCR community prevalence increased (adjusted odds ratio [OR] for P falciparum 0·63, 95% CI 0·57-0·69; adjusted OR for P vivax 0·52, 0·47-0·57). Factors associated with increasing P(Detect) included smaller catchment population size, high transmission season, improved care-seeking behaviour by infected individuals, and recent increases (within the previous year) in transmission intensity. INTERPRETATION: The proportion of all infections detected within health systems increases once transmission intensity is sufficiently low. The likely explanation for P falciparum is that reduced exposure to infection leads to lower levels of protective immunity in the population, increasing the likelihood that infected individuals will become symptomatic and seek care. These factors might also be true for P vivax but a better understanding of the transmission biology is needed to attribute likely reasons for the observed trend. In low transmission and pre-elimination settings, enhancing access to care and improvements in care-seeking behaviour of infected individuals will lead to an increased proportion of infections detected in the community and might contribute to accelerating the interruption of transmission. FUNDING: Wellcome Trust

Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models.

BACKGROUND: Serological data are increasingly being used to monitor malaria transmission intensity and have been demonstrated to be particularly useful in areas of low transmission where traditional measures such as EIR and parasite prevalence are limited. The seroconversion rate (SCR) is usually estimated using catalytic models in which the measured antibody levels are used to categorize individuals as seropositive or seronegative. One limitation of this approach is the requirement to impose a fixed cut-off to distinguish seropositive and negative individuals. Furthermore, the continuous variation in antibody levels is ignored thereby potentially reducing the precision of the estimate. METHODS: An age-specific density model which mimics antibody acquisition and loss was developed to make full use of the information provided by serological measures of antibody levels. This was fitted to blood-stage antibody density data from 12 villages at varying transmission intensity in Northern Tanzania to estimate the exposure rate as an alternative measure of transmission intensity. RESULTS: The results show a high correlation between the exposure rate estimates obtained and the estimated SCR obtained from a catalytic model (r = 0.95) and with two derived measures of EIR (r = 0.74 and r = 0.81). Estimates of exposure rate obtained with the density model were also more precise than those derived from catalytic models. CONCLUSION: This approach, if validated across different epidemiological settings, could be a useful alternative framework for quantifying transmission intensity, which makes more complete use of serological data

Acceptability, Feasibility, Drug Safety, and Effectiveness of a Pilot Mass Drug Administration with a Single Round of Sulfadoxine-Pyrimethamine Plus Primaquine and Indoor Residual Spraying in Communities with Malaria Transmission in Haiti, 2018.

For a malaria elimination strategy, Haiti's National Malaria Control Program piloted a mass drug administration (MDA) with indoor residual spraying (IRS) in 12 high-transmission areas across five communes after implementing community case management and strengthened surveillance. The MDA distributed sulfadoxine-pyrimethamine and single low-dose primaquine to eligible residents during house visits. The IRS campaign applied pirimiphos-methyl insecticide on walls of eligible houses. Pre- and post-campaign cross-sectional surveys were conducted to assess acceptability, feasibility, drug safety, and effectiveness of the combined interventions. Stated acceptability for MDA before the campaign was 99.2%; MDA coverage estimated at 10 weeks post-campaign was 89.6%. Similarly, stated acceptability of IRS at baseline was 99.9%; however, household IRS coverage was 48.9% because of the high number of ineligible houses. Effectiveness measured by Plasmodium falciparum prevalence at baseline and 10 weeks post-campaign were similar: 1.31% versus 1.43%, respectively. Prevalence of serological markers were similar at 10 weeks post-campaign compared with baseline, and increased at 6 months. No severe adverse events associated with the MDA were identified in the pilot; there were severe adverse events in a separate, subsequent campaign. Both MDA and IRS are acceptable and feasible interventions in Haiti. Although a significant impact of a single round of MDA/IRS on malaria transmission was not found using a standard pre- and post-intervention comparison, it is possible there was blunting of the peak transmission. Seasonal malaria transmission patterns, suboptimal IRS coverage, and low baseline parasitemia may have limited the effectiveness or the ability to measure effectiveness