Geostatistical modeling of malaria endemicity using serological indicators of exposure collected through school surveys

Comparison of new computational methods for spatial modelling of malaria

BACKGROUND

Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes. The appeal of faster methods is particularly great as the size of the region and number of spatial locations being modelled increases.

METHODS

This work presents an applied comparison of four proposed 'fast' computational methods for spatial modelling and the software provided to implement them-Integrated Nested Laplace Approximation (INLA), tree boosting with Gaussian processes and mixed effect models (GPBoost), Fixed Rank Kriging (FRK) and Spatial Random Forests (SpRF). The four methods are illustrated by estimating malaria prevalence on two different spatial scales-country and continent. The performance of the four methods is compared on these data in terms of accuracy, computation time, and ease of implementation.

RESULTS

Two of these methods-SpRF and GPBoost-do not scale well as the data size increases, and so are likely to be infeasible for larger-scale analysis problems. The two remaining methods-INLA and FRK-do scale well computationally, however the resulting model fits are very sensitive to the user's modelling assumptions and parameter choices. The binomial observation distribution commonly used for disease prevalence mapping with INLA fails to account for small-scale overdispersion present in the malaria prevalence data, which can lead to poor predictions. Selection of an appropriate alternative such as the Beta-binomial distribution is required to produce a reliable model fit. The small-scale random effect term in FRK overcomes this pitfall, but FRK model estimates are very reliant on providing a sufficient number and appropriate configuration of basis functions. Unfortunately the computation time for FRK increases rapidly with increasing basis resolution.

CONCLUSIONS

INLA and FRK both enable scalable geostatistical modelling of malaria prevalence data. However care must be taken when using both methods to assess the fit of the model to data and plausibility of predictions, in order to select appropriate model assumptions and parameters.

Serological evaluation of risk factors for exposure to malaria in a pre-elimination setting in Malaysian Borneo

Malaysia has reported no indigenous cases of P. falciparum and P. vivax for over 3 years. When transmission reaches such low levels, it is important to understand the individuals and locations where exposure risks are high, as they may be at greater risk in the case of a resurgence of transmission. Serology is a useful tool in low transmission settings, providing insight into exposure over longer durations than PCR or RDT. We ran blood samples from a 2015 population-based survey in northern Sabah, Malaysian Borneo on a multiplex bead assay. Using supervised machine learning methods, we characterised recent and historic exposure to Plasmodium falciparum and P. vivax and found recent exposure to P. falciparum to be very low, with exposure to both species increasing with age. We performed a risk-factor assessment on environmental, behavioural, demographic and household factors, and identified forest activity and longer travel times to healthcare as common risk-factors for exposure to P. falciparum and P. vivax. In addition, we used remote-sensing derived data and geostatistical models to assess environmental and spatial associations with exposure. We created predictive maps of exposure to recent P. falciparum in the study area and showed 3 clear foci of exposure. This study provides useful insight into the environmental, spatial and demographic risk factors for P. falciparum and P. vivax at a period of low transmission in Malaysian Borneo. The findings would be valuable in the case of resurgence of human malarias in the region.

Using Serological Markers for the Surveillance of Plasmodium vivax Malaria: A Scoping Review

The utilisation of serological surveillance methods for malaria has the potential to identify individuals exposed to Plasmodium vivax, including asymptomatic carriers. However, the application of serosurveillance varies globally, including variations in methodology and transmission context. No systematic review exists describing the advantages and disadvantages of utilising serosurveillance in various settings. Collation and comparison of these results is a necessary first step to standardise and validate the use of serology for the surveillance of P. vivax in specific transmission contexts. A scoping review was performed of P. vivax serosurveillance applications globally. Ninety-four studies were found that met predefined inclusion and exclusion criteria. These studies were examined to determine the advantages and disadvantages of serosurveillance experienced in each study. If studies reported seroprevalence results, this information was also captured. Measurement of antibodies serves as a proxy by which individuals exposed to P. vivax may be indirectly identified, including those with asymptomatic infections, which may be missed by other technologies. Other thematic advantages identified included the ease and simplicity of serological assays compared to both microscopy and molecular diagnostics. Seroprevalence rates varied widely from 0-93%. Methodologies must be validated across various transmission contexts to ensure the applicability and comparability of results. Other thematic disadvantages identified included challenges with species cross-reactivity and determining changes in transmission patterns in both the short- and long-term. Serosurveillance requires further refinement to be fully realised as an actionable tool. Some work has begun in this area, but more is required.

Serological Markers of Exposure to Plasmodium falciparum and Plasmodium vivax Infection in Southwestern Ethiopia

As malaria control and elimination efforts ramp up in Ethiopia, more sensitive tools for assessing exposure to coendemic Plasmodium falciparum and Plasmodium vivax are needed to accurately characterize malaria risk and epidemiology. Serological markers have been increasingly explored as cost-effective tools for measuring transmission intensity and evaluating intervention effectiveness. The objectives of this study were to evaluate the efficacy of a panel of 10 serological markers as a proxy for malaria exposure and to determine underlying risk factors of seropositivity. We conducted cross-sectional surveys in two sites of contrasting malaria transmission intensities in southwestern Ethiopia: Arjo in Oromia Region (low transmission) and Gambella in Gambella Regional State (moderate transmission). We measured antibody reactivity against six P. falciparum (AMA-1, CSP, EBA175RIII-V, MSP-142, MSP-3, RH2ab) and four P. vivax (DBPII[Sal1], EBP2, MSP-119, RBP2b) targets. We used mixed effects logistic regressions to assess predictors of seropositivity. Plasmodium spp. infection prevalence by quantitative polymerase chain reaction was 1.36% in Arjo and 10.20% in Gambella. Seroprevalence and antibody levels against all 10 antigens were higher in Gambella than in Arjo. We observed spatial heterogeneities in seroprevalence across Arjo and smaller variations across Gambella. Seroprevalence in both sites was lowest against PfCSP and highest against PfAMA-1, PfMSP-142, and PvMSPS-119. Male sex, age, and agricultural occupation were positively associated with seropositivity in Arjo; associations were less pronounced in Gambella. Our findings demonstrate that seroprevalence and antibody levels to specific Plasmodium antigens can be used to identify high-risk groups and geographical areas where interventions to reduce malaria transmission should be implemented.

Combining school-catchment area models with geostatistical models for analysing school survey data from low-resource settings: Inferential benefits and limitations

School-based sampling has been used to inform targeted responses for malaria and neglected tropical diseases. Standard geostatistical methods for mapping disease prevalence use the school location to model spatial correlation, which is questionable since exposure to the disease is more likely to occur in the residential location. In this paper, we propose to overcome the limitations of standard geostatistical methods by introducing a modelling framework that accounts for the uncertainty in the location of the residence of the students. By using cost distance and cost allocation models to define spatial accessibility and in absence of any information on the travel mode of students to school, we consider three school catchment area models that assume walking only, walking and bicycling and, walking and motorized transport. We illustrate the use of this approach using two case studies of malaria in Kenya and compare it with the standard approach that uses the school locations to build geostatistical models. We argue that the proposed modelling framework presents several inferential benefits, such as the ability to combine data from multiple surveys some of which may also record the residence location, and to deal with ecological bias when estimating the effects of malaria risk factors. However, our results show that invalid assumptions on the modes of travel to school can worsen the predictive performance of geostatistical models. Future research in this area should focus on collecting information on the modes of transportation to school which can then be used to better parametrize the catchment area models.

Identification of factors associated with residual malaria transmission using school-based serological surveys in settings pursuing elimination

Background

Targeted research on residual malaria transmission is important to improve strategies in settings pursuing elimination, where transmission reductions prove challenging. This study aimed to detect and characterize spatial heterogeneity and factors associated with Plasmodium falciparum infections and exposure, P. falciparum apical membrane antigen 1 (PfAMA1) antibody (Ab) response, in the Central Highlands of Madagascar (CHL).

Methods

From May to July 2014, a cross-sectional school-based survey was carried out in 182 fokontany (villages) within 7 health districts of the CHL. Rapid diagnostic tests (RDTs) and a bead-based immunoassay including PfAMA1 antigen biomarker were used to estimate malaria prevalence and seroprevalence, respectively. Local Moran’s I index was used to detect spatial “hotspots”. Remotely sensed environmental data—temperature, vegetation indices, land covers, and elevation—were used in multivariable mixed-effects logistic regression models to characterize factors associated with malaria infection and cumulative exposure.

Results

Among 6,293 school-children ages 2–14 years surveyed, RDT prevalence was low at 0.8% (95% CI 0.6–1.1%), while PfAMA1 Ab seroprevalence was 7.0% (95% CI 6.4–7.7%). Hotspots of PfAMA1 Ab seroprevalence were observed in two districts (Ankazobe and Mandoto). Seroprevalence increased for children living > 5 km from a health centre (adjusted odds ratio (OR) = 1.6, 95% CI 1.2–2.2), and for those experiencing a fever episode in the previous 2 weeks (OR 1.7, 95% CI 1.2–2.4), but decreased at higher elevation (for each 100-m increase, OR = 0.7, 95% CI 0.6–0.8). A clear age pattern was observed whereby children 9–10 years old had an OR of 1.8 (95% CI 1.2–2.4), children 11–12 years an OR of 3.7 (95% CI 2.8–5.0), and children 13–14 years an OR of 5.7 (95% CI 4.0–8.0) for seropositivity, compared with younger children (2–8 years).

Conclusion

The use of serology in this study provided a better understanding of malaria hotspots and associated factors, revealing a pattern of higher transmission linked to geographical barriers in health care access. The integration of antibody-assays into existing surveillance activities could improve exposure assessment, and may help to monitor the effectiveness of malaria control efforts and adapt elimination interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04260-0.

Characterizing the spatial distribution of multiple malaria diagnostic endpoints in a low-transmission setting in Lao PDR

The epidemiology of malaria changes as prevalence falls in low-transmission settings, with remaining infections becoming more difficult to detect and diagnose. At this stage active surveillance is critical to detect residual hotspots of transmission. However, diagnostic tools used in active surveillance generally only detect concurrent infections, and surveys may benefit from sensitive tools such as serological assays. Serology can be used to interrogate and characterize individuals' previous exposure to malaria over longer durations, providing information essential to the detection of remaining foci of infection. We ran blood samples collected from a 2016 population-based survey in the low-transmission setting of northern Lao PDR on a multiplexed bead assay to characterize historic and recent exposures to Plasmodium falciparum and vivax. Using geostatistical methods and remote-sensing data we assessed the environmental and spatial associations with exposure, and created predictive maps of exposure within the study sites. We additionally linked the active surveillance PCR and serology data with passively collected surveillance data from health facility records. We aimed to highlight the added information which can be gained from serology as a tool in active surveillance surveys in low-transmission settings, and to identify priority areas for national surveillance programmes where malaria risk is higher. We also discuss the issues faced when linking malaria data from multiple sources using multiple diagnostic endpoints.

Characterising spatial patterns of neglected tropical disease transmission using integrated sero-surveillance in Northern Ghana

Background

As prevalence decreases in pre-elimination settings, identifying the spatial distribution of remaining infections to target control measures becomes increasingly challenging. By measuring multiple antibody responses indicative of past exposure to different pathogens, integrated serological surveys enable simultaneous characterisation of residual transmission of multiple pathogens.

Methodology/Principal findings

Here, we combine integrated serological surveys with geostatistical modelling and remote sensing-derived environmental data to estimate the spatial distribution of exposure to multiple diseases in children in Northern Ghana. The study utilised the trachoma surveillance survey platform (cross-sectional two-stage cluster-sampled surveys) to collect information on additional identified diseases at different stages of elimination with minimal additional cost. Geostatistical modelling of serological data allowed identification of areas with high probabilities of recent exposure to diseases of interest, including areas previously unknown to control programmes. We additionally demonstrate how serological surveys can be used to identify areas with exposure to multiple diseases and to prioritise areas with high uncertainty for future surveys. Modelled estimates of cluster-level prevalence were strongly correlated with more operationally feasible metrics of antibody responses.

Conclusions/Significance

This study demonstrates the potential of integrated serological surveillance to characterise spatial distributions of exposure to multiple pathogens in low transmission and elimination settings when the probability of detecting infections is low.

Mapping the endemicity and seasonality of clinical malaria for intervention targeting in Haiti using routine case data

Towards the goal of malaria elimination on Hispaniola, the National Malaria Control Program of Haiti and its international partner organisations are conducting a campaign of interventions targeted to high-risk communities prioritised through evidence-based planning. Here we present a key piece of this planning: an up-to-date, fine-scale endemicity map and seasonality profile for Haiti informed by monthly case counts from 771 health facilities reporting from across the country throughout the 6-year period from January 2014 to December 2019. To this end, a novel hierarchical Bayesian modelling framework was developed in which a latent, pixel-level incidence surface with spatio-temporal innovations is linked to the observed case data via a flexible catchment sub-model designed to account for the absence of data on case household locations. These maps have focussed the delivery of indoor residual spraying and focal mass drug administration in the Grand’Anse Department in South-Western Haiti.

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.

A unified and flexible modelling framework for the analysis of malaria serology data

Serology data are an increasingly important tool in malaria surveillance, especially in low transmission settings where the estimation of parasite-based indicators is often problematic. Existing methods rely on the use of thresholds to identify seropositive individuals and estimate transmission intensity, while making assumptions about the temporal dynamics of malaria transmission that are rarely questioned. Here, we present a novel threshold-free approach for the analysis of malaria serology data which avoids dichotomization of continuous antibody measurements and allows us to model changes in the antibody distribution across age in a more flexible way. The proposed unified mechanistic model combines the properties of reversible catalytic and antibody acquisition models, and allows for temporally varying boosting and seroconversion rates. Additionally, as an alternative to the unified mechanistic model, we also propose an empirical approach to analysis where modelling of the age-dependency is informed by the data rather than biological assumptions. Using serology data from Western Kenya, we demonstrate both the usefulness and limitations of the novel modelling framework.

Enhanced Health Facility Surveys to Support Malaria Control and Elimination across Different Transmission Settings in the Philippines

Following substantial progress in malaria control in the Philippines, new surveillance approaches are needed to identify and target residual malaria transmission. This study evaluated an enhanced surveillance approach using rolling cross-sectional surveys of all health facility attendees augmented with molecular diagnostics and geolocation. Facility surveys were carried out in three sites representing different transmission intensities: Morong, Bataan (pre-elimination), Abra de Ilog, Occidental Mindoro (stable medium risk), and Rizal, Palawan (high risk, control). Only one rapid diagnostic test (RDT)–positive infection and no PCR confirmed infections were found in Bataan and Occidental Mindoro, suggesting the absence of transmission. In Palawan, the inclusion of all health facility attendees, regardless of symptoms, and use of molecular diagnostics identified 313 infected individuals in addition to 300 cases identified by routine screening of febrile patients with the RDT or microscopy. Of these, the majority (313/613) were subpatent infections and only detected using molecular methods. Simultaneous collection of GPS coordinates on tablet-based applications allowed real-time mapping of malaria infections. Risk factor analysis showed higher risks in children and indigenous groups, with bed net use having a protective effect. Subpatent infections were more common in men and older age-groups. Overall, malaria risks were not associated with participants’ classification, and some of the non-patient clinic attendees reported febrile illnesses (1.9%, 26/1,369), despite not seeking treatment, highlighting the widespread distribution of infection in communities. Together, these data illustrate the utility of health facility–based surveys to augment surveillance data to increase the probability of detecting infections in the wider community.

Use of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings

BACKGROUND

Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.

RESULTS

Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.

CONCLUSIONS

Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

Quantifying malaria endemicity in Ethiopia through combined application of classical methods and enzyme-linked immunosorbent assay: an initial step for countries with low transmission initiating elimination programme

Background

In the context of reduced transmission of malaria, it is essential to re-evaluate and determine the level of transmission as it guides re-orientation of control measures which is appropriate to local disease epidemiology. However, little is known about level of malaria transmission in Ethiopia. The present study aimed to investigate the level of malaria transmission through combined application of classical methods and enzyme-linked immunosorbent assay (EIA) in low transmission settings of Ethiopia.

Methods

This study was conducted in June 2016 on 763 apparently healthy children 2–9 years of age. Children were recruited from ten sites representing different malaria transmission settings in Ethiopia. Splenomegaly rate, infection rate and EIA antibody test were used to determine endemicity. The data were analysed using SPSS 21.0 and Stata 12.0.

Results

The overall prevalence of malaria parasitaemia was 2.49% (95% CI 1.38–3.59) and 2.36% (95% CI 1.28–3.44) as detected using rapid diagnostic test and microscopy, respectively. Plasmodium falciparum accounted for 62.63% of the infections. The prevalence of parasitaemia significantly varied by altitude and localities; the highest (5.8%) in areas below 1500 m above sea level. Overall, splenomegaly rate was 1.70% (95% CI 0.78–0.2.66%), making the overall malaria transmission hypoendemic. Infection rate was higher among males (2.7%), but rate of splenomegaly was higher in females. Incongruent with spleen rate and parasitaemia, EIA showed a higher level of cumulative exposure to malaria with spatially localized and highly heterogeneous transmission. Overall, 126 (18.75%, 95% CI 15.79–21.71) of the children were positive for total malaria antibodies with significant variations with altitude, age and sex; the higher in areas of < 1500 m asl (25.8%), children ≥ 5 years (22.1%) and among males (20.9%).

Conclusions

Splenomegaly and parasitaemia are not good measures to show variations in the levels of malaria transmission in reduced and/or low endemic settings. The malaria antibody (i.e. serological) test seems to be a good measure of malaria endemicity showing greater degree of heterogeneity and localized risk of transmission. Thus, malaria elimination efforts need to be supported with serological indicators to identify patterns of foci of transmission to set priorities for interventions.

The malERA Refresh Consultative Panel on Combination Interventions and Modelling. malERA: An updated research agenda for combination interventions and modelling in malaria elimination and eradication

This paper summarises key advances and priorities since the 2011 presentation of the Malaria Eradication Research Agenda (malERA), with a focus on the combinations of intervention tools and strategies for elimination and their evaluation using modelling approaches. With an increasing number of countries embarking on malaria elimination programmes, national and local decisions to select combinations of tools and deployment strategies directed at malaria elimination must address rapidly changing transmission patterns across diverse geographic areas. However, not all of these approaches can be systematically evaluated in the field. Thus, there is potential for modelling to investigate appropriate 'packages' of combined interventions that include various forms of vector control, case management, surveillance, and population-based approaches for different settings, particularly at lower transmission levels. Modelling can help prioritise which intervention packages should be tested in field studies, suggest which intervention package should be used at a particular level or stratum of transmission intensity, estimate the risk of resurgence when scaling down specific interventions after local transmission is interrupted, and evaluate the risk and impact of parasite drug resistance and vector insecticide resistance. However, modelling intervention package deployment against a heterogeneous transmission background is a challenge. Further validation of malaria models should be pursued through an iterative process, whereby field data collected with the deployment of intervention packages is used to refine models and make them progressively more relevant for assessing and predicting elimination outcomes.

Proximity to vector breeding site and risk of Plasmodium vivax infection: a prospective cohort study in rural Ethiopia

Background

Despite falling incidence and mortality since the turn of the century, malaria remains an important global health challenge. In the future fight against malaria, greater emphasis will have to be placed on understanding and addressing malaria caused by the Plasmodium vivax parasite. Unfortunately, due to years of neglect and underfunding, there are currently many gaps in knowledge of P. vivax malaria. The aims of the present study were to explore the association between distance to vector breeding site and P. vivax infection in rural Ethiopia, and, secondarily, to test whether this association varies with age.

Methods

A prospective, cohort study of all residents in the Chano Mille Kebele in southern Ethiopia from April 2009 to March 2011 (n = 8121). Weekly household follow up visits included screening for febrile cases (active surveillance). Participants were also asked to contact the local health centre if they experienced subjective fever between visits (passive surveillance). Plasmodium vivax infection was confirmed using microscopy by two independent readers. Information was collected on demographics and household characteristics including GPS-determined distance to vector breeding site. Data was analysed using Cox regression modelling.

Results

Overall the P. vivax infection rate was 12.3/1000 person-years (95% CI 10.5–14.5). Mean household distance to breeding site was 2449 m (range 1646–3717 m). Fully adjusted results showed very strong evidence of an association between proximity to breeding site and P. vivax infection: rate ratio = 3.47 (95% CI 2.15–5.60; P < 0.001) comparing the group closest to the breeding site (distance < 2100 m; n = 1383) to the group furthest away (distance > 2700 m; n = 2460). There was no evidence that age was an effect modifier in the association.

Conclusion

Results showed strong evidence that household proximity to vector breeding site is positively associated with P. vivax infection in rural Ethiopia, and that this association is constant across age groups. The findings might influence how net-distribution and indoor residual spraying campaigns are planned, help guide strategies on water resource development by highlighting potential health effects of man-made dams near human habitats, and add to current educational information given to people living close to breeding sites.

Current and cumulative malaria infections in a setting embarking on elimination: Amhara, Ethiopia

Background

Since 2005, Ethiopia has aggressively scaled up malaria prevention and case management. As a result, the number of malaria cases and deaths has significantly declined. In order to track progress towards the elimination of malaria in Amhara Region, coverage of malaria control tools and current malaria transmission need to be documented.

Methods

A cross-sectional household survey oversampling children under 5 years of age was conducted during the dry season in 2013. A bivalent rapid diagnostic test (RDT) detecting both Plasmodium falciparum and Plasmodium vivax and serology assays using merozoite antigens from both these species were used to assess the prevalence of malaria infections and exposure to malaria parasites in 16 woredas (districts) in Amhara Region.

Results

7878 participants were included, with a mean age of 16.8 years (range 0.5–102.8 years) and 42.0% being children under 5 years of age. The age-adjusted RDT-positivity for P. falciparum and P. vivax infection was 1.5 and 0.4%, respectively, of which 0.05% presented as co-infections. Overall age-adjusted seroprevalence was 30.0% for P. falciparum, 21.8% for P. vivax, and seroprevalence for any malaria species was 39.4%. The prevalence of RDT-positive infections varied by woreda, ranging from 0.0 to 8.3% and by altitude with rates of 3.2, 0.7, and 0.4% at under 2000, 2000–2500, and >2500 m, respectively. Serological analysis showed heterogeneity in transmission intensity by area and altitude and evidence for a change in the force of infection in the mid-2000s.

Conclusions

Current and historic malaria transmission across Amhara Region show substantial variation by age and altitude with some settings showing very low or near-zero transmission. Plasmodium vivax infections appear to be lower but relatively more stable across geography and altitude, while P. falciparum is the dominant infection in the higher transmission, low-altitude areas. Age-dependent seroprevalence analyses indicates a drop in transmission occurred in the mid-2000s, coinciding with malaria control scale-up efforts. As malaria parasitaemia rates get very low with elimination efforts, serological evaluation may help track progress to elimination.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-017-1884-y) contains supplementary material, which is available to authorized users.

Impact of metric and sample size on determining malaria hotspot boundaries

The spatial heterogeneity of malaria suggests that interventions may be targeted for maximum impact. It is unclear to what extent different metrics lead to consistent delineation of hotspot boundaries. Using data from a large community-based malaria survey in the western Kenyan highlands, we assessed the agreement between a model-based geostatistical (MBG) approach to detect hotspots using Plasmodium falciparum parasite prevalence and serological evidence for exposure. Malaria transmission was widespread and highly heterogeneous with one third of the total population living in hotspots regardless of metric tested. Moderate agreement (Kappa = 0.424) was observed between hotspots defined based on parasite prevalence by polymerase chain reaction (PCR)- and the prevalence of antibodies to two P. falciparum antigens (MSP-1, AMA-1). While numerous biologically plausible hotspots were identified, their detection strongly relied on the proportion of the population sampled. When only 3% of the population was sampled, no PCR derived hotspots were reliably detected and at least 21% of the population was needed for reliable results. Similar results were observed for hotspots of seroprevalence. Hotspot boundaries are driven by the malaria diagnostic and sample size used to inform the model. These findings warn against the simplistic use of spatial analysis on available data to target malaria interventions in areas where hotspot boundaries are uncertain.

The shape of the iceberg: quantification of submicroscopic Plasmodium falciparum and Plasmodium vivax parasitaemia and gametocytaemia in five low endemic settings in Ethiopia

BACKGROUND

The widespread presence of low-density asymptomatic infections with concurrent gametocytes may be a stumbling block for malaria elimination. This study investigated the asymptomatic reservoir of Plasmodium falciparum and Plasmodium vivax infections in schoolchildren from five settings in northwest Ethiopia.

METHODS

Two cross-sectional surveys were conducted in June and November 2015, enrolling 551 students from five schools and 294 students from three schools, respectively. Finger prick whole blood and plasma samples were collected. The prevalence and density of P. falciparum and P. vivax parasitaemia and gametocytaemia were determined by 18S rRNA quantitative PCR (qPCR) and pfs25 and pvs25 reverse transcriptase qPCR. Antibodies against blood stage antigens apical membrane antigen-1 (AMA-1) and merozoite surface protein-1 (MSP-1₁₉) were measured for both species.

RESULTS

Whilst only 6 infections were detected by microscopy in 881 slides (0.7%), 107 of 845 blood samples (12.7%) were parasite positive by (DNA-based) qPCR. qPCR parasite prevalence between sites and surveys ranged from 3.8 to 19.0% for P. falciparum and 0.0 to 9.0% for P. vivax. The median density of P. falciparum infections (n = 85) was 24.4 parasites/µL (IQR 18.0-34.0) and the median density of P. vivax infections (n = 28) was 16.4 parasites/µL (IQR 8.8-55.1). Gametocyte densities by (mRNA-based) qRT-PCR were strongly associated with total parasite densities for both P. falciparum (correlation coefficient = 0.83, p = 0.010) and P. vivax (correlation coefficient = 0.58, p = 0.010). Antibody titers against P. falciparum AMA-1 and MSP-1₁₉ were higher in individuals who were P. falciparum parasite positive in both surveys (p < 0.001 for both comparisons).

DISCUSSION

This study adds to the available evidence on the wide-scale presence of submicroscopic parasitaemia by quantifying submicroscopic parasite densities and concurrent gametocyte densities. There was considerable heterogeneity in the occurrence of P. falciparum and P. vivax infections and serological markers of parasite exposure between the examined low endemic settings in Ethiopia.

Mapping Malaria Risk in Low Transmission Settings: Challenges and Opportunities

As malaria transmission declines, it becomes increasingly focal and prone to outbreaks. Understanding and predicting patterns of transmission risk becomes an important component of an effective elimination campaign, allowing limited resources for control and elimination to be targeted cost-effectively. Malaria risk mapping in low transmission settings is associated with some unique challenges. This article reviews the main challenges and opportunities related to risk mapping in low transmission areas including recent advancements in risk mapping low transmission malaria, relevant metrics, and statistical approaches and risk mapping in post-elimination settings.

Geo-spatial factors associated with infection risk among young children in rural Ghana: a secondary spatial analysis

Background

Determining the spatial patterns of infection among young children living in a malaria-endemic area may provide a means of locating high-risk populations who could benefit from additional resources for treatment and improved access to healthcare. The objective of this secondary analysis of baseline data from a cluster-randomized trial among 1943 young Ghanaian children (6–35 months of age) was to determine the geo-spatial factors associated with malaria and non-malaria infection status.

Methods

Spatial analyses were conducted using a generalized linear geostatistical model with a Matern spatial correlation function and four definitions of infection status using different combinations of inflammation (C-reactive protein, CRP > 5 mg/L) and malaria parasitaemia (with or without fever). Potentially informative variables were included in a final model through a series of modelling steps, including: individual-level variables (Model 1); household-level variables (Model 2); and, satellite-derived spatial variables (Model 3). A final (Model 4) and maximal model (Model 5) included a set of selected covariates from Models 1 to 3.

Results

The final models indicated that children with inflammation (CRP > 5 mg/L) and/or any evidence of malaria parasitaemia at baseline were more likely to be under 2 years of age, stunted, wasted, live further from a health facility, live at a lower elevation, have less educated mothers, and higher ferritin concentrations (corrected for inflammation) compared to children without inflammation or parasitaemia. Similar results were found when infection was defined as clinical malaria or parasitaemia with/without fever (definitions 3 and 4). Conversely, when infection was defined using CRP only, all covariates were non-significant with the exception of baseline ferritin concentration. In Model 5, all infection definitions that included parasitaemia demonstrated a significant interaction between normalized difference vegetation index and land cover type. Maps of the predicted infection probabilities and spatial random effect showed defined high- and low-risk areas that tended to coincide with elevation and cluster around villages.

Conclusions

The risk of infection among young children in a malaria-endemic area may have a predictable spatial pattern which is associated with geographical characteristics, such as elevation and distance to a health facility.

Original trial registration clinicaltrials.gov (NCT01001871)

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1388-1) contains supplementary material, which is available to authorized users.

Analysis of age-dependent trends in Ov16 IgG4 seroprevalence to onchocerciasis

Background

Diagnostics provide a means to measure progress toward disease elimination. Many countries in Africa are approaching elimination of onchocerciasis after successful implementation of mass drug administration programs as well as vector control. An understanding of how markers for infection such as skin snip microfilaria and Onchocerca volvulus-specific seroconversion perform in near-elimination settings informs how to best use these markers.

Methods

All-age participants from 35 villages in Togo were surveyed in 2013 and 2014 for skin snip Onchocerca volvulus microfilaria and IgG4 antibody response by enzyme-linked immunosorbent assay (ELISA) to the Onchocerca volvulus-specific antigen Ov16. A Gaussian mixture model applying the expectation-maximization (EM) algorithm was used to determine seropositivity from Ov16 ELISA data. For a subset of participants (n = 434), polymerase chain reaction (PCR) was performed on the skin snips taken during surveillance.

Results

Within the 2,005 participants for which there was Ov16 ELISA data, O. volvulus microfilaremia prevalence and Ov16 seroprevalence were, 2.5 and 19.7 %, respectively, in the total population, and 1.6 and 3.6 % in children under 11. In the subset of 434 specimens for which ELISA, PCR, and microscopy data were generated, it was found that in children under 11 years of age, the anti-Ov16 IgG4 antibody response demonstrate a sensitivity and specificity of 80 and 97 %, respectively, against active infections as determined by combined PCR and microscopy on skin snips. Further analysis was performed in 34 of the 35 villages surveyed. These villages were stratified by all-age seroprevalence into three clusters: < 15 %; 15–20 %; and > 20 %. Age-dependence of seroprevalence for each cluster was best reflected by a two-phase force-of-infection (FOI) catalytic model. In all clusters, the lower of the two phases of FOI was associated with a younger age group, as reflected by the seroconversion rates for each phase. The age at which transition from lower to higher seroconversion, between the two phases of FOI, was found to be highest (older) for the cluster of villages with < 15 % seroprevalence and lowest (younger) for the cluster with the highest all-age seroprevalence.

Conclusions

The anti-Ov16 IgG4 antibody response is an accurate marker for active infection in children under 11 years of age in this population. Applying Ov16 surveillance to a broader age range provides additional valuable information for understanding progression toward elimination and can inform where targeted augmented interventions may be needed. Clustering of villages by all-age sero-surveillance allowed application of a biphasic FOI model to differentiate seroconversion rates for different age groups within the village cluster categories.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-016-1623-1) contains supplementary material, which is available to authorized users.