Human mobility patterns and malaria importation on Bioko Island

Genetic surveillance reveals low but sustained malaria transmission with clonal replacement in Sao Tome and Principe

BACKGROUND

Despite efforts to eliminate malaria in Sao Tome and Principe (STP), cases have recently increased. Understanding residual transmission structure is crucial for developing effective elimination strategies.

METHODS

This study collected surveillance data and generated amplicon sequencing data from 980 samples between 2010 and 2016 to examine the genetic structure of the parasite population.

RESULTS

Here we show that the mean multiplicity of infection (MOI) is 1.3, with 11% polyclonal infections, indicating low transmission intensity. Temporal trends of these genetic metrics do not align with incidence rates, suggesting that changes in genetic metrics may not straightforwardly reflect changes in transmission intensity, particularly in low transmission settings where genetic drift and importation have a substantial impact. While 88% of samples are genetically linked, continuous turnover in genetic clusters and changes in drug-resistance haplotypes are observed. Principal component analysis reveals some STP samples are genetically similar to those from Central and West Africa, indicating possible importation.

CONCLUSIONS

These findings highlight the need to prioritize several interventions, such as targeted interventions against transmission hotspots, reactive case detection, and strategies to reduce the introduction of new parasites into this island nation as it approaches elimination. This study also serves as a case study for implementing genetic surveillance in a low transmission setting.

Integrating local malaria molecular monitoring into regular malaria indicator surveys on Bioko Island: high association between urban communities and low-density infections

BACKGROUND

Effective malaria control requires accurate identification of Plasmodium infections to tailor interventions appropriately. Rapid diagnostic tests (RDTs) are crucial tools for this purpose due to their small size and ease-of-use functionality. These tests typically target the Plasmodium falciparum histidine-rich protein 2 (HRP2) antigen. However, some strains of P. falciparum have deletions in the hrp2 and hrp3 genes, which may result in a false negative diagnosis using HRP2-based RDTs. Additionally, RDTs have a detection limit of 100 parasites per microlitre, insufficient for identifying low-density infections that sustain malaria transmission. This study explores integrating molecular monitoring using a novel cartridge-based PCR test, PlasmoPod, using samples from a malaria indicator survey (MIS) on Bioko Island, Equatorial Guinea to enhance detection of low-density infections and inform targeted malaria control strategies.

METHODS

The study utilized a combination of RDTs and the DiaxxoPCR device for molecular monitoring. The device DiaxxoPCR uses a prefilled cartridge system, termed PlasmoPod for a malaria-based assay that employs a qPCR assay targeting 18S rDNA/rRNA. Samples from the 2023 MIS were extracted from dried blood spots (DBS), qPCR run in duplicate on the PlasmoPod. Epidemiological data from the MIS were merged with molecular data and the association between MIS variables to malaria infection by qPCR, and low-density infections were measured.

RESULTS

The integration of molecular monitoring revealed a proportion of low-density infections that circumvented RDTs diagnosis. Notably, individuals in urban communities and those reporting recent fever were more likely to harbour low-density, asymptomatic malaria infections. Findings suggest that urban residents, although less associated to malaria infection than rural residents by both RDT and qPCR, may be serving as a transmission reservoir. The relationship between low-density infections and individuals who recently reported fever may reflect recent anti-malarial treatment or natural clearance, and thus have lingering parasites in their blood.

CONCLUSION

The study highlights the limitations of HRP2-based RDTs in detecting low density infections and underscores the potential of molecular tools like PlasmoPod in malaria surveillance. By identifying elusive transmission reservoirs and tracking parasite importation, molecular monitoring can play a crucial role in achieving malaria elimination. The findings advocate for the broader implementation of molecular diagnostics in malaria programs, especially in areas with low transmission, to enhance the detection and targeting of hidden reservoirs of infection.

Estimating the potential impact of surveillance test-and-treat posts to reduce malaria in border regions in sub-Saharan Africa: a modelling study

BACKGROUND

The last malaria cases in near-elimination settings are often found in international border regions due to the presence of hard-to-reach populations, conflict, uneven intervention coverage, and human migration. Test-and-treat border posts are an under-researched form of active case detection used to interrupt transmission chains between countries.

METHODS

An individual-based, mathematical metapopulation model of Plasmodium falciparum was used to estimate the effectiveness of border screening posts on total cases in malaria-endemic sub-Saharan Africa.

RESULTS

The implementation of international border posts across 401 sub-national administrative units would avert a median of 7173 (IQR 1075 to 23,550) cases per unit over a 10 year period and reduce PfPR2-10 by a median of 0.21% (IQR 0.04 to 0.44%).

CONCLUSIONS

Border posts were most effective in low-transmission settings with high-transmission neighbours. Border posts alone in sub-Saharan Africa will not allow a country to reach elimination, particularly when considering feasibility and acceptability, but could contribute to broader control packages to targeted populations.

Climate Change and Malaria: A Call for Robust Analytics

Mosquito ecology and behavior and malaria parasite development display marked sensitivity to weather, in particular to temperature and precipitation. Therefore, climate change is expected to profoundly affect malaria epidemiology in its transmission, spatiotemporal distribution and consequent disease burden. However, malaria transmission is also complicated by other factors (e.g. urbanization, socioeconomic development, genetics, drug resistance) which together constitute a highly complex, dynamical system, where the influence of any single factor can be masked by others. In this study, we therefore aim to re-evaluate the evidence underlying the widespread belief that climate change will increase worldwide malaria transmission. We review two broad types of study that have contributed to this evidence-base: i) studies that project changes in transmission due to inferred relationships between environmental and mosquito entomology, and ii) regression-based studies that look for associations between environmental variables and malaria prevalence. We then employ a simple statistical model to show that environmental variables alone do not account for the observed spatiotemporal variation in malaria prevalence. Our review raises several concerns about the robustness of the analyses used for advocacy around climate change and malaria. We find that, while climate change's effect on malaria is highly plausible, empirical evidence is much less certain. Future research on climate change and malaria must become integrated into malaria control programs, and understood in context as one factor among many. Our work outlines gaps in modelling that we believe are priorities for future research.

Human mobility and malaria risk in peri-urban and rural communities in the Peruvian Amazon

BACKGROUND

While the global burden of malaria cases has decreased over the last two decades, the disease remains a major international threat, even on the rise in many regions. More than 85% of Peruvian malaria cases are in the Amazonian region of Loreto. Internal mobility primarily related to occupation is thought to be primarily responsible for maintaining endemicity and introducing and reintroducing malaria parasites into areas of anophelism, a challenge for malaria eradication. This study focuses on identifying the sources of malaria transmission and patterns of human mobility in order to understand the movement and transmission of the parasite.

METHODS

The assessment of connectivity produced by human mobility was evaluated in three districts of Loreto, through 10 cross-sectional population screening from 2018 to 2020. We used social network analysis (SNA) to obtain weighted and unweighted degrees of connectivity and explore its variability by socio-demographic characteristics. In addition, we integrated travel history and malaria incidence data to estimate parasite connectivity due to internal human mobility between locations. Finally, we used logistic multivariate regressions to explore the factors associated with Plasmodium spp. infection in mobile individuals.

RESULTS

We found that internal human mobility results in high connectivity between communities from the Mazan, Iquitos, and San Juan Bautista districts. We identified nearby destinations that may act as sinks or sources for malaria transmission, including densely populated towns and rural campsites. In addition, we found that being a male, traveling to rural campsites, and working outdoors are associated with Plasmodium spp. infection in travelers from the Mazan district.

CONCLUSIONS

We provide compelling evidence about how human mobility connects rural communities in the Peruvian Amazon. Using SNA, we uncovered district-specific patterns and destinations, providing further evidence of human mobility heterogeneity in the region. To address the challenge of human mobility and malaria in this setting, geographic heterogeneity of malaria transmission must be considered.

The challenge of improving long-lasting insecticidal nets coverage on Bioko Island: using data to adapt distribution strategies

BACKGROUND

Since 2015, malaria vector control on Bioko Island has relied heavily upon long-lasting insecticidal nets (LLIN) to complement other interventions. Despite significant resources utilised, however, achieving and maintaining high coverage has been elusive. Here, core LLIN indicators were used to assess and redefine distribution strategies.

METHODS

LLIN indicators were estimated for Bioko Island between 2015 and 2022 using a 1x1 km grid of areas. The way these indicators interacted was used to critically assess coverage targets. Particular attention was paid to spatial heterogeneity and to differences between urban Malabo, the capital, and the rural periphery.

RESULTS

LLIN coverage according to all indicators varied substantially across areas, decreased significantly soon after mass distribution campaigns (MDC) and, with few exceptions, remained consistently below the recommended target. Use was strongly correlated with population access, particularly in Malabo. After a change in strategy in Malabo from MDC to fixed distribution points, use-to-access showed significant improvement, indicating those who obtained their nets from these sources were more likely to keep them and use them. Moreover, their use rates were significantly higher than those of whom sourced their nets elsewhere.

CONCLUSIONS

Striking a better balance between LLIN distribution efficiency and coverage represents a major challenge as LLIN retention and use rates remain low despite high access resulting from MDC. The cost-benefit of fixed distribution points in Malabo revealed significant advantages, offering a viable alternative for ensuring access to LLINs to those who use them.

Impact of six-month COVID-19 travel moratorium on Plasmodium falciparum prevalence on Bioko Island, Equatorial Guinea

Importation of malaria infections is a suspected driver of sustained malaria prevalence on areas of Bioko Island, Equatorial Guinea. Quantifying the impact of imported infections is difficult because of the dynamic nature of the disease and complexity of designing a randomized trial. We leverage a six-month travel moratorium in and out of Bioko Island during the initial COVID-19 pandemic response to evaluate the contribution of imported infections to malaria prevalence on Bioko Island. Using a difference in differences design and data from island wide household surveys conducted before (2019) and after (2020) the travel moratorium, we compare the change in prevalence between areas of low historical travel to those with high historical travel. Here, we report that in the absence of a travel moratorium, the prevalence of infection in high travel areas was expected to be 9% higher than observed, highlighting the importance of control measures that target imported infections.

Climate change, malaria and neglected tropical diseases: a scoping review

To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

Genetic surveillance reveals low, sustained malaria transmission with clonal replacement in Sao Tome and Principe

Despite efforts to eliminate malaria in Sao Tome and Principe (STP), cases have recently increased. Understanding residual transmission structure is crucial for developing effective elimination strategies. This study collected surveillance data and generated amplicon sequencing data from 980 samples between 2010 and 2016 to examine the genetic structure of the parasite population. The mean multiplicity of infection (MOI) was 1.3, with 11% polyclonal infections, indicating low transmission intensity. Temporal trends of these genetic metrics did not align with incidence rates, suggesting that changes in genetic metrics may not straightforwardly reflect changes in transmission intensity, particularly in low transmission settings where genetic drift and importation have a substantial impact. While 88% of samples were genetically linked, continuous turnover in genetic clusters and changes in drug-resistance haplotypes were observed. Principal component analysis revealed some STP samples were genetically similar to those from Central and West Africa, indicating possible importation. These findings highlight the need to prioritize several interventions such as targeted interventions against transmission hotspots, reactive case detection, and strategies to reduce the introduction of new parasites into this island nation as it approaches elimination. This study also serves as a case study for implementing genetic surveillance in a low transmission setting.

Malaria seroepidemiology in very low transmission settings in the Peruvian Amazon

Despite progress towards malaria reduction in Peru, measuring exposure in low transmission areas is crucial for achieving elimination. This study focuses on two very low transmission areas in Loreto (Peruvian Amazon) and aims to determine the relationship between malaria exposure and proximity to health facilities. Individual data was collected from 38 villages in Indiana and Belen, including geo-referenced households and blood samples for microscopy, PCR and serological analysis. A segmented linear regression model identified significant changes in seropositivity trends among different age groups. Local Getis-Ord Gi* statistic revealed clusters of households with high (hotspots) or low (coldspots) seropositivity rates. Findings from 4000 individuals showed a seropositivity level of 2.5% (95%CI: 2.0%-3.0%) for P. falciparum and 7.8% (95%CI: 7.0%-8.7%) for P. vivax, indicating recent or historical exposure. The segmented regression showed exposure reductions in the 40-50 age group (β1 = 0.043, p = 0.003) for P. vivax and the 50-60 age group (β1 = 0.005, p = 0.010) for P. falciparum. Long and extreme distance villages from Regional Hospital of Loreto exhibited higher malaria exposure compared to proximate and medium distance villages (p < 0.001). This study showed the seropositivity of malaria in two very low transmission areas and confirmed the spatial pattern of hotspots as villages become more distant.

Mathematical modeling of malaria transmission dynamics in humans with mobility and control states

Malaria importation is one of the hypothetical drivers of malaria transmission dynamics across the globe. Several studies on malaria importation focused on the effect of the use of conventional malaria control strategies as approved by the World Health Organization (WHO) on malaria transmission dynamics but did not capture the effect of the use of traditional malaria control strategies by vigilant humans. In order to handle the aforementioned situation, a novel system of Ordinary Differential Equations (ODEs) was developed comprising the human and the malaria vector compartments. Analysis of the system was carried out to assess its quantitative properties. The novel computational algorithm used to solve the developed system of ODEs was implemented and benchmarked with the existing Runge-Kutta numerical solution method. Furthermore, simulations of different vigilant conditions useful to control malaria were carried out. The novel system of malaria models was well-posed and epidemiologically meaningful based on its quantitative properties. The novel algorithm performed relatively better in terms of model simulation accuracy than Runge-Kutta. At the best model-fit condition of 98% vigilance to the use of conventional and traditional malaria control strategies, this study revealed that malaria importation has a persistent impact on malaria transmission dynamics. In lieu of this, this study opined that total vigilance to the use of the WHO-approved and traditional malaria management tools would be the most effective control strategy against malaria importation.

HM, Brady OJ, Guerra CA, García GA, Carter AR, Ferguson HM, Afolabi BE, Hay SI, Reiner RC, Kiware S, Smith DL. Spatial dynamics of malaria transmission

The Ross-Macdonald model has exerted enormous influence over the study of malaria transmission dynamics and control, but it lacked features to describe parasite dispersal, travel, and other important aspects of heterogeneous transmission. Here, we present a patch-based differential equation modeling framework that extends the Ross-Macdonald model with sufficient skill and complexity to support planning, monitoring and evaluation for Plasmodium falciparum malaria control. We designed a generic interface for building structured, spatial models of malaria transmission based on a new algorithm for mosquito blood feeding. We developed new algorithms to simulate adult mosquito demography, dispersal, and egg laying in response to resource availability. The core dynamical components describing mosquito ecology and malaria transmission were decomposed, redesigned and reassembled into a modular framework. Structural elements in the framework-human population strata, patches, and aquatic habitats-interact through a flexible design that facilitates construction of ensembles of models with scalable complexity to support robust analytics for malaria policy and adaptive malaria control. We propose updated definitions for the human biting rate and entomological inoculation rates. We present new formulas to describe parasite dispersal and spatial dynamics under steady state conditions, including the human biting rates, parasite dispersal, the "vectorial capacity matrix," a human transmitting capacity distribution matrix, and threshold conditions. An [Formula: see text] package that implements the framework, solves the differential equations, and computes spatial metrics for models developed in this framework has been developed. Development of the model and metrics have focused on malaria, but since the framework is modular, the same ideas and software can be applied to other mosquito-borne pathogen systems.

Mapping malaria incidence using routine health facility surveillance data in Uganda

INTRODUCTION

Maps of malaria risk are important tools for allocating resources and tracking progress. Most maps rely on cross-sectional surveys of parasite prevalence, but health facilities represent an underused and powerful data source. We aimed to model and map malaria incidence using health facility data in Uganda.

METHODS

Using 24 months (2019-2020) of individual-level outpatient data collected from 74 surveillance health facilities located in 41 districts across Uganda (n=445 648 laboratory-confirmed cases), we estimated monthly malaria incidence for parishes within facility catchment areas (n=310) by estimating care-seeking population denominators. We fit spatio-temporal models to the incidence estimates to predict incidence rates for the rest of Uganda, informed by environmental, sociodemographic and intervention variables. We mapped estimated malaria incidence and its uncertainty at the parish level and compared estimates to other metrics of malaria. To quantify the impact that indoor residual spraying (IRS) may have had, we modelled counterfactual scenarios of malaria incidence in the absence of IRS.

RESULTS

Over 4567 parish-months, malaria incidence averaged 705 cases per 1000 person-years. Maps indicated high burden in the north and northeast of Uganda, with lower incidence in the districts receiving IRS. District-level estimates of cases correlated with cases reported by the Ministry of Health (Spearman's r=0.68, p<0.0001), but were considerably higher (40 166 418 cases estimated compared with 27 707 794 cases reported), indicating the potential for underreporting by the routine surveillance system. Modelling of counterfactual scenarios suggest that approximately 6.2 million cases were averted due to IRS across the study period in the 14 districts receiving IRS (estimated population 8 381 223).

CONCLUSION

Outpatient information routinely collected by health systems can be a valuable source of data for mapping malaria burden. National Malaria Control Programmes may consider investing in robust surveillance systems within public health facilities as a low-cost, high benefit tool to identify vulnerable regions and track the impact of interventions.

Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions

BACKGROUND

Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach.

METHODS

This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year.

RESULTS

Malaria prevalence was higher in 10-14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year.

CONCLUSIONS

Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island.

How long is the last mile? Evaluating successful malaria elimination trajectories

BACKGROUND

Many national malaria programmes have set goals of eliminating malaria, but realistic timelines for achieving this goal remain unclear. In this investigation, historical data are collated on countries that successfully eliminated malaria to assess how long elimination has taken in the past, and thus to inform feasible timelines for achieving it in the future.

METHODS

Annual malaria case series were sought for 56 successful elimination programmes through a non-systematic review. Up to 40 years of annual case counts were compiled leading up to the first year in which zero locally acquired or indigenous cases were reported. To separate the period over which effective elimination efforts occurred from prior background trends, annual case totals were log transformed, and their slopes evaluated for a breakpoint in linear trend using the segmented package in R. The number of years from the breakpoint to the first year with zero cases and the decline rate over that period were then calculated. Wilcox-Mann-Whitney tests were used to evaluate whether a set of territory characteristics were associated with the timelines and decline rates.

RESULTS

Case series declining to the first year with zero cases were compiled for 45/56 of the candidate elimination programmes, and statistically significant breakpoints were identified for 42. The median timeline from the breakpoint to the first year with zero local cases was 12 years, over which cases declined at a median rate of 54% per year. Prior to the breakpoint, the median trend was slightly decreasing with median annual decline of < 3%. Timelines to elimination were fastest among territories that lacked land boundaries, had centroids in the Tropics, received low numbers of imported cases, and had elimination certified by the World Health Organization.

CONCLUSION

The historical case series assembled here may help countries with aspirations of malaria elimination to set feasible milestones towards this goal. Setting goals for malaria elimination on short timescales may be most appropriate in isolated, low importation settings, such as islands, while other regions aiming to eliminate malaria must consider how to sustainably fund and maintain vital case management and vector control services until zero cases are reached.

Molecular Surveillance of Artemisinin-Based Combination Therapies Resistance in Plasmodium falciparum Parasites from Bioko Island, Equatorial Guinea

Artemisinin-based combination therapies (ACTs) resistance has emerged and could be diffusing in Africa. As an offshore island on the African continent, the island of Bioko in Equatorial Guinea is considered severely affected and resistant to drug-resistant Plasmodium falciparum malaria. However, the spatial and temporal distribution remain unclear. Molecular monitoring targeting the Pfcrt, Pfk13, Pfpm2, and Pfmdr1 genes was conducted to provide insight into the impact of current antimalarial drug resistance on the island. Furthermore, polymorphic characteristics, haplotype network, and the effect of natural selection of the Pfk13 gene were evaluated. A total of 152 Plasmodium falciparum samples (collected from 2017 to 2019) were analyzed for copy number variation of the Pfpm2 gene and Pfk13, Pfcrt, and Pfmdr1 mutations. Statistical analysis of Pfk13 sequences was performed following different evolutionary models using 96 Bioko sequences and 1322 global sequences. The results showed that the prevalence of Pfk13, Pfcrt, and Pfmdr1 mutations was 73.68%, 78.29%, and 75.66%, respectively. Large proportions of isolates with multiple copies of Pfpm2 were observed (67.86%). In Bioko parasites, the genetic diversity of Pfk13 was low, and purifying selection was suggested by Tajima's D test (-1.644, P > 0.05) and the dN/dS test (-0.0004438, P > 0.05). The extended haplotype homozygosity analysis revealed that Pfk13_K189T, although most frequent in Africa, has not yet conferred a selective advantage for parasitic survival. The results suggested that the implementation of continuous drug monitoring on Bioko Island is an essential measure. IMPORTANCE Malaria, one of the tropical parasitic diseases with a high transmission rate in Bioko Island, Equatorial Guinea, especially caused by P. falciparum is highly prevalent in this region and is commonly treated locally with ACTs. The declining antimalarial susceptibility of artemisinin-based drugs suggested that resistance to artemisinin and its derivatives is developing in P. falciparum. Copy number variants in Pfpm2 and genetic polymorphisms in Pfk13, Pfcrt, and Pfmdr1 can be used as risk assessment indicators to track the development and spread of drug resistance. This study reported for the first time the molecular surveillance of Pfpm2, Pfcrt, Pfk13, and Pfmdr1 genes in Bioko Island from 2017 to 2019 to assess the possible risk of local drug-resistant P. falciparum.

Characterising co-infections with Plasmodium spp., Mansonella perstans or Loa loa in asymptomatic children, adults and elderly people living on Bioko Island using nucleic acids extracted from malaria rapid diagnostic tests

Background

Regular and comprehensive epidemiological surveys of the filarial nematodes Mansonella perstans and Loa loa in children, adolescents and adults living across Bioko Island, Equatorial Guinea are lacking. We aimed to demonstrate that blood retained on malaria rapid diagnostic tests, commonly deployed for malaria surveys, could be used as a source of nucleic acids for molecular based detection of M. perstans and L. loa. We wanted to determine the positivity rate and distribution of filarial nematodes across different age groups and geographical areas as well as to understand level of co-infections with malaria in an asymptomatic population.

Methodology

M. perstans, L. loa and Plasmodium spp. parasites were monitored by qPCR in a cross-sectional study using DNA extracted from a subset malaria rapid diagnostic tests (mRDTs) collected during the annual malaria indicator survey conducted on Bioko Island in 2018.

Principal findings

We identified DNA specific for the two filarial nematodes investigated among 8.2% (263) of the 3214 RDTs screened. Positivity rates of M. perstans and L. loa were 6.6% and 1.5%, respectively. M. perstans infection were more prominent in male (10.5%) compared to female (3.9%) survey participants. M. perstans parasite density and positivity rate was higher among older people and the population living in rural areas. The socio-economic status of participants strongly influenced the infection rate with people belonging to the lowest socio-economic quintile more than 3 and 5 times more likely to be L. loa and M. perstans infected, respectively. No increased risk of being co-infected with Plasmodium spp. parasites was observed among the different age groups.

Conclusions/Significance

We found otherwise asymptomatic individuals were infected with M. perstans and L. loa. Our study demonstrates that employing mRDTs probed with blood for malaria testing represents a promising, future tool to preserve and ship NAs at room temperature to laboratories for molecular, high-throughput diagnosis and genotyping of blood-dwelling nematode filarial infections. Using this approach, asymptomatic populations can be reached and surveyed for infectious diseases beyond malaria.

Mansonella perstans and Loa loa are filarial nematodes that infect millions of people living in less developed areas, predominantly in sub-Saharan Africa. Both parasites are neglected among other filarial nematodes because both are regarded as causing mainly asymptomatic infections. The aim of this study was to explore the feasibility of using malaria rapid diagnostic tests (mRDTs) deployed during malaria surveys as a convenient sampling strategy for molecular surveillance of blood-dwelling filarial nematode infections. Our findings demonstrate the potential of mRDTs as a source of parasite DNA beyond malaria, providing an opportunity to expand current knowledge on the distribution and populations mostly affected by M. perstans and L. loa infections to Equatorial Guinea, located in Central-West Africa.

Analysis of nucleic acids extracted from rapid diagnostic tests reveals a significant proportion of false positive test results associated with recent malaria treatment

BACKGROUND

Surveillance programmes often use malaria rapid diagnostic tests (RDTs) to determine the proportion of the population carrying parasites in their peripheral blood to assess the malaria transmission intensity. Despite an increasing number of reports on false-negative and false-positive RDT results, there is a lack of systematic quality control activities for RDTs deployed in malaria surveillance programmes.

METHODS

The diagnostic performance of field-deployed RDTs used for malaria surveys was assessed by retrospective molecular analysis of the blood retained on the tests.

RESULTS

Of the 2865 RDTs that were collected in 2018 on Bioko Island and analysed in this study, 4.7% had a false-negative result. These false-negative RDTs were associated with low parasite density infections. In 16.6% of analysed samples, masked pfhrp2 and pfhrp3 gene deletions were identified, in which at least one Plasmodium falciparum strain carried a gene deletion. Among all positive RDTs analysed, 28.4% were tested negative by qPCR and therefore considered to be false-positive. Analysing the questionnaire data collected from the participants, this high proportion of false-positive RDTs could be explained by P. falciparum histidine rich protein 2 (PfHRP2) antigen persistence after recent malaria treatment.

CONCLUSION

Malaria surveillance depending solely on RDTs needs well-integrated quality control procedures to assess the extent and impact of reduced sensitivity and specificity of RDTs on malaria control programmes.

Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering

Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal—a region of exceptionally low malaria transmission (entomological inoculation rate less than 1). Genetic identity (identity by state, IBS) was established using a 24-single nucleotide polymorphism molecular barcode, identity by descent was calculated from whole genome sequence data, and a hierarchical Bayesian regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts.

Dynamic changes in genetic diversity, drug resistance mutations, and treatment outcomes of falciparum malaria from the low-transmission to the pre-elimination phase on the islands of São Tomé and Príncipe

Background

With effective vector control and case management, substantial progress has been made towards eliminating malaria on the islands of São Tomé and Príncipe (STP). This study assessed the dynamic changes in the genetic diversity of Plasmodium falciparum, the anti-malarial drug resistance mutations, and malaria treatment outcomes between 2010 and 2016 to provide insights for the prevention of malaria rebounding.

Methods

Polymorphic regions of merozoite surface proteins 1 and 2 (msp1 and msp2) were sequenced in 118 dried blood spots (DBSs) collected from malaria patients who had visited the Central Hospital in 2010–2016. Mutations in the multi-drug resistance I (pfmdr1), chloroquine resistance transporter (pfcrt), and kelch 13 (pfk13) genes were analysed by polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) and sequencing in 111 DBSs. A total of 7482 cases that completed a 28-day follow-up were evaluated for treatment outcomes based on the microscopic results. Regression models were used to characterize factors associated with levels of parasite density and treatment failures.

Results

Parasite strains in STP showed significant changes during and after the peak incidence in 2012. The prevalent allelic type in msp1 changed from K1 to MAD20, and that in msp2 changed from 3D7/IC to FC27. The dominant alleles of drug-resistance markers were pfmdr1 86Y, 184F, D1246, and pfcrt 76 T (Y-F-D-T, 51.4%). The average parasite density in malaria cases declined threefold from low-transmission (2010–2013) to pre-elimination period (2014–2016). Logistic regression models showed that patients with younger age (OR for age = 0.97–0.98, p < 0.001), higher initial parasite density (log₁₀-transformed, OR = 1.44, p < 0.001), and receiving quinine treatment (compared to artemisinin-based combination therapy, OR = 1.91–1.96, p < 0.001) were more likely to experience treatment failures during follow-up.

Conclusions

Plasmodium falciparum in STP had experienced changes in prevalent strains, and increased mutation frequencies in drug-resistance genes from the low-transmission to the pre-elimination settings. Notably, patients with younger age and receiving quinine treatment were more likely to show parasitological treatment failure during follow-up. Therapeutic efficacy should be carefully monitored to inform future treatment policy in STP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-04007-3.

Low parasite connectivity among three malaria hotspots in Thailand

Identifying sources and sinks of malaria transmission is critical for designing effective intervention strategies particularly as countries approach elimination. The number of malaria cases in Thailand decreased 90% between 2012 and 2020, yet elimination has remained a major public health challenge with persistent transmission foci and ongoing importation. There are three main hotspots of malaria transmission in Thailand: Ubon Ratchathani and Sisaket in the Northeast; Tak in the West; and Yala in the South. However, the degree to which these hotspots are connected via travel and importation has not been well characterized. Here, we develop a metapopulation model parameterized by mobile phone call detail record data to estimate parasite flow among these regions. We show that parasite connectivity among these regions was limited, and that each of these provinces independently drove the malaria transmission in nearby provinces. Overall, our results suggest that due to the low probability of domestic importation between the transmission hotspots, control and elimination strategies can be considered separately for each region.

Measuring the accuracy of gridded human population density surfaces: A case study in Bioko Island, Equatorial Guinea

Background

Geospatial datasets of population are becoming more common in models used for health policy. Publicly-available maps of human population make a consistent picture from inconsistent census data, and the techniques they use to impute data makes each population map unique. Each mapping model explains its methods, but it can be difficult to know which map is appropriate for which policy work. High quality census datasets, where available, are a unique opportunity to characterize maps by comparing them with truth.

Methods

We use census data from a bed-net mass-distribution campaign on Bioko Island, Equatorial Guinea, conducted by the Bioko Island Malaria Elimination Program as a gold standard to evaluate LandScan (LS), WorldPop Constrained (WP-C) and WorldPop Unconstrained (WP-U), Gridded Population of the World (GPW), and the High-Resolution Settlement Layer (HRSL). Each layer is compared to the gold-standard using statistical measures to evaluate distribution, error, and bias. We investigated how map choice affects burden estimates from a malaria prevalence model.

Results

Specific population layers were able to match the gold-standard distribution at different population densities. LandScan was able to most accurately capture highly urban distribution, HRSL and WP-C matched best at all other lower population densities. GPW and WP-U performed poorly everywhere. Correctly capturing empty pixels is key, and smaller pixel sizes (100 m vs 1 km) improve this. Normalizing areas based on known district populations increased performance. The use of differing population layers in a malaria model showed a disparity in results around transition points between endemicity levels.

Discussion

The metrics in this paper, some of them novel in this context, characterize how these population maps differ from the gold standard census and from each other. We show that the metrics help understand the performance of a population map within a malaria model. The closest match to the census data would combine LandScan within urban areas and the HRSL for rural areas. Researchers should prefer particular maps if health calculations have a strong dependency on knowing where people are not, or if it is important to categorize variation in density within a city.

Quantifying malaria acquired during travel and its role in malaria elimination on Bioko Island

BACKGROUND

Malaria elimination is the goal for Bioko Island, Equatorial Guinea. Intensive interventions implemented since 2004 have reduced prevalence, but progress has stalled in recent years. A challenge for elimination has been malaria infections in residents acquired during travel to mainland Equatorial Guinea. The present article quantifies how off-island contributes to remaining malaria prevalence on Bioko Island, and investigates the potential role of a pre-erythrocytic vaccine in making further progress towards elimination.

METHODS

Malaria transmission on Bioko Island was simulated using a model calibrated based on data from the Malaria Indicator Surveys (MIS) from 2015 to 2018, including detailed travel histories and malaria positivity by rapid-diagnostic tests (RDTs), as well as geospatial estimates of malaria prevalence. Mosquito population density was adjusted to fit local transmission, conditional on importation rates under current levels of control and within-island mobility. The simulations were then used to evaluate the impact of two pre-erythrocytic vaccine distribution strategies: mass treat and vaccinate, and prophylactic vaccination for off-island travellers. Lastly, a sensitivity analysis was performed through an ensemble of simulations fit to the Bayesian joint posterior probability distribution of the geospatial prevalence estimates.

RESULTS

The simulations suggest that in Malabo, an urban city containing 80% of the population, there are some pockets of residual transmission, but a large proportion of infections are acquired off-island by travellers to the mainland. Outside of Malabo, prevalence was mainly attributable to local transmission. The uncertainty in the local transmission vs. importation is lowest within Malabo and highest outside. Using a pre-erythrocytic vaccine to protect travellers would have larger benefits than using the vaccine to protect residents of Bioko Island from local transmission. In simulations, mass treatment and vaccination had short-lived benefits, as malaria prevalence returned to current levels as the vaccine's efficacy waned. Prophylactic vaccination of travellers resulted in longer-lasting reductions in prevalence. These projections were robust to underlying uncertainty in prevalence estimates.

CONCLUSIONS

The modelled outcomes suggest that the volume of malaria cases imported from the mainland is a partial driver of continued endemic malaria on Bioko Island, and that continued elimination efforts on must account for human travel activity.

Incidence of Plasmodium falciparum malaria infection in 6-month to 45-year-olds on selected areas of Bioko Island, Equatorial Guinea

Background

Extensive malaria control measures have been implemented on Bioko Island, Equatorial Guinea over the past 16 years, reducing parasite prevalence and malaria-related morbidity and mortality, but without achieving elimination. Malaria vaccines offer hope for reducing the burden to zero. Three phase 1/2 studies have been conducted successfully on Bioko Island to evaluate the safety and efficacy of whole Plasmodium falciparum (Pf) sporozoite (SPZ) malaria vaccines. A large, pivotal trial of the safety and efficacy of the radiation-attenuated Sanaria^® PfSPZ Vaccine against P. falciparum is planned for 2022. This study assessed the incidence of malaria at the phase 3 study site and characterized the influence of socio-demographic factors on the burden of malaria to guide trial design.

Methods

A cohort of 240 randomly selected individuals aged 6 months to 45 years from selected areas of North Bioko Province, Bioko Island, was followed for 24 weeks after clearance of parasitaemia. Assessment of clinical presentation consistent with malaria and thick blood smears were performed every 2 weeks. Incidence of first and multiple malaria infections per person-time of follow-up was estimated, compared between age groups, and examined for associated socio-demographic risk factors.

Results

There were 58 malaria infection episodes observed during the follow up period, including 47 first and 11 repeat infections. The incidence of malaria was 0.25 [95% CI (0.19, 0.32)] and of first malaria was 0.23 [95% CI (0.17, 0.30)] per person per 24 weeks (0.22 in 6–59-month-olds, 0.26 in 5–17-year-olds, 0.20 in 18–45-year-olds). Incidence of first malaria with symptoms was 0.13 [95% CI (0.09, 0.19)] per person per 24 weeks (0.16 in 6–59-month-olds, 0.10 in 5–17-year-olds, 0.11 in 18–45-year-olds). Multivariate assessment showed that study area, gender, malaria positivity at screening, and household socioeconomic status independently predicted the observed incidence of malaria.

Conclusion

Despite intensive malaria control efforts on Bioko Island, local transmission remains and is spread evenly throughout age groups. These incidence rates indicate moderate malaria transmission which may be sufficient to support future larger trials of PfSPZ Vaccine. The long-term goal is to conduct mass vaccination programmes to halt transmission and eliminate P. falciparum malaria.

Clustering of subpatent infections in households with asymptomatic rapid diagnostic test-positive cases in Bioko Island, Equatorial Guinea independent of travel to regions of higher malaria endemicity: a cross-sectional study

Background

Prevalence of falciparum malaria on Bioko Island remains high despite sustained, intensive control. Progress may be hindered by high proportions of subpatent infections that are not detected by rapid diagnostic tests (RDT) but contribute to onward transmission, and by imported infections. Better understanding of the relationship between subpatent infections and RDT-detected infections, and whether this relationship is different from imported versus locally acquired infections, is imperative to better understand the sources of infection and mechanisms of transmission to tailor more effective interventions.

Methods

Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed on a sub-set of samples from the 2015 Malaria Indicator Survey to identify subpatent infections. Households with RDT(+) individuals were matched 1:4 with households with no RDT(+) individuals. The association between living in a household with an RDT(+) individual and having a subpatent infection was evaluated using multivariate hierarchical logistic regression models with inverse probability weights for selection. To evaluate possible modification of the association by potential importation of the RDT(+) case, the analysis was repeated among strata of matched sets based on the reported eight-week travel history of the RDT(+) individual(s).

Results

There were 142 subpatent infections detected in 1,400 individuals (10.0%). The prevalence of subpatent infections was higher in households with versus without an RDT(+) individual (15.0 vs 9.1%). The adjusted prevalence odds of subpatent infection were 2.59-fold greater (95% CI: 1.31, 5.09) for those in a household with an RDT(+) individual compared to individuals in a household without RDT(+) individuals. When stratifying by travel history of the RDT(+) individual, the association between subpatent infections and RDT(+) infections was stronger in the strata in which the RDT(+) individual(s) had not recently travelled (adjusted prevalence odds ratio (aPOR) 2.95; 95% CI:1.17, 7.41), and attenuated in the strata in which recent travel was reported (aPOR 1.76; 95% CI: 0.54, 5.67).

Conclusions

There is clustering of subpatent infections around RDT(+) individual(s) when both imported and local infection are suspected. Future control strategies that aim to treat whole households in which an RDT(+) individual is found may target a substantial portion of infections that would otherwise not be detected.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03844-6.

Analysing human population movement data for malaria control and elimination

BACKGROUND

Human population movement poses a major obstacle to malaria control and elimination. With recent technological advances, a wide variety of data sources and analytical methods have been used to quantify human population movement (HPM) relevant to control and elimination of malaria.

METHODS

The relevant literature and selected studies that had policy implications that could help to design or target malaria control and elimination interventions were reviewed. These studies were categorized according to spatiotemporal scales of human mobility and the main method of analysis.

RESULTS

Evidence gaps exist for tracking routine cross-border HPM and HPM at a regional scale. Few studies accounted for seasonality. Out of twenty included studies, two studies which tracked daily neighbourhood HPM used descriptive analyses as the main method, while the remaining studies used statistical analyses or mathematical modelling.

CONCLUSION

Although studies quantified varying types of human population movement covering different spatial and temporal scales, methodological gaps remain that warrant further studies related to malaria control and elimination.

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.

Comparing metapopulation dynamics of infectious diseases under different models of human movement

Newly available datasets present exciting opportunities to investigate how human population movement contributes to the spread of infectious diseases across large geographical distances. It is now possible to construct realistic models of infectious disease dynamics for the purposes of understanding global-scale epidemics. Nevertheless, a remaining unanswered question is how best to leverage the new data to parameterize models of movement, and whether one's choice of movement model impacts modeled disease outcomes. We adapt three well-studied models of infectious disease dynamics, the susceptible-infected-recovered model, the susceptible-infected-susceptible model, and the Ross-Macdonald model, to incorporate either of two candidate movement models. We describe the effect that the choice of movement model has on each disease model's results, finding that in all cases, there are parameter regimes where choosing one movement model instead of another has a profound impact on epidemiological outcomes. We further demonstrate the importance of choosing an appropriate movement model using the applied case of malaria transmission and importation on Bioko Island, Equatorial Guinea, finding that one model produces intelligible predictions of R ₀, whereas the other produces nonsensical results.

Genetic diversity and natural selection on the thrombospondin-related adhesive protein (TRAP) gene of Plasmodium falciparum on Bioko Island, Equatorial Guinea and global comparative analysis

BACKGROUND

Thrombospondin-related adhesive protein (TRAP) is a transmembrane protein that plays a crucial role during the invasion of Plasmodium falciparum into liver cells. As a potential malaria vaccine candidate, the genetic diversity and natural selection of PfTRAP was assessed and the global PfTRAP polymorphism pattern was described.

METHODS

153 blood spot samples from Bioko malaria patients were collected during 2016-2018 and the target TRAP gene was amplified. Together with the sequences from database, nucleotide diversity and natural selection analysis, and the structural prediction were preformed using bioinformatical tools.

RESULTS

A total of 119 Bioko PfTRAP sequences were amplified successfully. On Bioko Island, PfTRAP shows its high degree of genetic diversity and heterogeneity, with π value for 0.01046 and Hd for 0.99. The value of dN-dS (6.2231, p < 0.05) hinted at natural selection of PfTRAP on Bioko Island. Globally, the African PfTRAPs showed more diverse than the Asian ones, and significant genetic differentiation was discovered by the fixation index between African and Asian countries (Fst > 0.15, p < 0.05). 667 Asian isolates clustered in 136 haplotypes and 739 African isolates clustered in 528 haplotypes by network analysis. The mutations I116T, L221I, Y128F, G228V and P299S were predicted as probably damaging by PolyPhen online service, while mutations L49V, R285G, R285S, P299S and K421N would lead to a significant increase of free energy difference (ΔΔG > 1) indicated a destabilization of protein structure.

CONCLUSIONS

Evidences in the present investigation supported that PfTRAP gene from Bioko Island and other malaria endemic countries is highly polymorphic (especially at T cell epitopes), which provided the genetic information background for developing an PfTRAP-based universal effective vaccine. Moreover, some mutations have been shown to be detrimental to the protein structure or function and deserve further study and continuous monitoring.

The use of islands and cluster-randomized trials to investigate vector control interventions: a case study on the Bijagós archipelago, Guinea-Bissau

Vector-borne diseases threaten the health of populations around the world. While key interventions continue to provide protection from vectors, there remains a need to develop and test new vector control tools. Cluster-randomized trials, in which the intervention or control is randomly allocated to clusters, are commonly selected for such evaluations, but their design must carefully consider cluster size and cluster separation, as well as the movement of people and vectors, to ensure sufficient statistical power and avoid contamination of results. Island settings present an opportunity to conduct these studies. Here, we explore the benefits and challenges of conducting intervention studies on islands and introduce the Bijagós archipelago of Guinea-Bissau as a potential study site for interventions intended to control vector-borne diseases. This article is part of the theme issue 'Novel control strategies for mosquito-borne diseases'.

Decreasing trend of imported malaria cases but increasing influx of mixed P. falciparum and P. vivax infections in malaria-free Kuwait

Malaria still continues to be the most important parasitic disease worldwide, affecting 228 million people and causing 405,000 deaths each year. In this retrospective study during 2013 to 2018, we documented the incidence of imported malaria infection and evaluated the impact of malaria preventive measures in Kuwait, a non-endemic country. The epidemiologic and demographic data of all malaria cases was collected from the Infectious Diseases Hospital, Kuwait where all suspected cases of malaria are referred for confirmation and therapeutic intervention. The diagnosis of malaria infection was done by microscopy of Giemsa stained blood films. Selected samples were retested with BinaxNOW^® Malaria rapid test and molecular assay to reconfirm the Plasmodium spp. or mixed infection. Overall, 1913 (25.9%) malaria cases were detected, 81.5% of which were among male subjects. Male subjects had higher incidence of P. vivax malaria (113; 91.1%) and mixed infection with P. falciparum and P. vivax (1245; 90.0%) compared to females who had higher rate of P. falciparum infection (52.4%). An overwhelming majority of malaria cases (1895; 99.1%) were detected among expatriates from malaria-endemic countries; India (1012; 52.9%), Pakistan (390; 20.4%), Afghanistan (94; 4.9%) and African countries (313; 16.3%). Only 18 cases involved Kuwaiti nationals, all with a history of travel to African countries. The majority of malaria cases were detected during the summer and fall months (May-October). Our data showed that the incidence rate of imported malaria cases was stable during 2013 to 2018, however, the incidence of total malaria cases showed a declining trend over the years. This study confirms that the preventive program has been successful in reducing the incidence of imported malaria infections in Kuwait. The most striking finding of this study was high incidence of mixed infection with P. falciparum and P. vivax, with almost all (97%) cases among workers from India.

Describing the current status of Plasmodium falciparum population structure and drug resistance within mainland Tanzania using molecular inversion probes

High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programmes, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania countrywide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, approximately separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from nearby districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts (including two infections carrying pfk13-R561H), and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared.

Human mobility and urban malaria risk in the main transmission hotspot of Amazonian Brazil

Malaria in the Amazon is often perceived as an exclusively rural disease, but transmission has been increasingly documented within and near urban centers. Here we explore patterns and causes of urban-to-rural mobility, which places travelers at risk of malaria in Mâncio Lima, the main malaria hotspot in northwestern Brazil. We also analyze rural-to-urban mobility caused by malaria treatment seeking, which poses an additional risk of infection to urban residents. We show that the rural localities most frequently visited by urban residents–typically farming settlements in the vicinity of the town–are those with the most intense malaria transmission and also the most frequent source localities of imported malaria cases diagnosed in the town. The most mobile urban residents are typically poor males 16 to 60-years old from multi-sited households who lack a formal job. Highly mobile residents represent a priority target for more intensive and effective malaria control interventions, that cannot be readily delivered to the entire community, in this and similar urbanized endemic settings across the Amazon.

Association between recent overnight travel and use of long-lasting insecticidal nets in rural Uganda: a prospective cohort study in Tororo

Background

The burden of malaria in Uganda remains high, but has become increasingly heterogenous following intensified malaria control. Travel within Uganda is recognized as a risk factor for malaria, but behaviours associated with travel are not well-understood. To address this knowledge gap, malaria-relevant behaviours of cohort participants were assessed during travel and at home in Uganda.

Methods

Residents from 80 randomly selected households in Nagongera sub-county, Tororo district were enrolled into a cohort to study malaria in rural Uganda. All participants were given long-lasting insecticidal nets (LLINs) at enrolment and were evaluated every 4 weeks at the study clinic. Participants were asked if they had travelled overnight from their home, and if so, a questionnaire was administered to capture information on travel details and behaviours. Behaviour while travelling was assessed within 4 weeks following travel during the study clinic visit. Behaviour while at home was assessed using a similar questionnaire during two-weekly home visits. Behaviours while travelling vs at home were compared using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual. Analysis of factors associated with LLIN adherence, such as destination and duration of travel, time to bed during travel, gender and age at time of travel, were assessed using log binomial regression models with generalized estimating equations adjusting for repeated measures in the same individual.

Results

Between October 2017 and October 2019, 527 participants were enrolled and assessed for travel. Of these, 123 (23.2%) reported taking 211 overnight trips; 149 (70.6%) trips were within Tororo. Participants were less likely to use LLINs when travelling than when at home (41.0% vs. 56.2%, relative risk [RR] 0.73, 95% CI 0.60–0.89, p = 0.002); this difference was noted for women (38.8% vs 59.2%, RR 0.66, 95% CI 0.52–0.83, p = 0.001) but not men (48.3% vs 46.6%, RR 0.96, 95% CI 0.67–1.40, p = 0.85). In an adjusted analysis, factors associated with LLIN use when travelling included destination (travelling to districts not receiving indoor residual spraying [IRS] 65.8% vs Tororo district 32.2%, RR 1.80, 95% CI 1.31–2.46, p < 0.001) and duration of travel (> 7 nights 60.3% vs one night 24.4%, RR 1.97, 95% CI 1.07–3.64, p = 0.03).

Conclusions

Travellers, particularly women, were less likely to use LLINs when travelling than when at home. LLIN adherence was higher among those who travelled to non-IRS districts and for more than 1 week, suggesting that perceived malaria risk influences LLIN use. Strategies are needed to raise awareness of the importance of using LLINs while travelling.

The Equatoguinean Malaria Vaccine Initiative: From the Launching of a Clinical Research Platform to Malaria Elimination Planning in Central West Africa

Fifteen years of investment in malaria control on Bioko Island, Equatorial Guinea (EG), dramatically reduced malaria-associated morbidity and mortality, but the impact has plateaued. To progress toward elimination, EG is investing in the development of a malaria vaccine. We assessed the unique public–private partnership that has had such a significant impact on malaria on Bioko Island and now added a major effort on malaria vaccine development. As part of a $79M commitment, the EG government (75%) and three American energy companies (25%) have invested since 2012 greater than $55M in the Equatoguinean Malaria Vaccine Initiative (EGMVI) to support clinical development of Sanaria^® PfSPZ vaccines (Sanaria Inc., Rockville, MD). In turn, the vaccine development program is building human capital and physical capacity. The EGMVI established regulatory and ethical oversight to ensure compliance with the International Conference on Harmonization and Good Clinical Practices for the first importation of investigational product, ethical approval, and conduct of a clinical trial in Equatoguinean history. The EGMVI has completed three vaccine trials in EG, two vaccine trials in Tanzania, and a malaria incidence study, and initiated preparations for a 2,100-volunteer clinical trial. Personnel are training for advanced degrees abroad and have been trained in Good Clinical Practices and protocol-specific methods. A new facility has established the foundation for a national research institute. Biomedical research and development within this visionary, ambitious public–private partnership is fostering major improvements in EG. The EGMVI plans to use a PfSPZ Vaccine alongside standard malaria control interventions to eliminate Pf malaria from Bioko, becoming a potential model for elimination campaigns elsewhere.

The risk of malaria infection for travelers visiting the Brazilian Amazonian region: A mathematical modeling approach

BACKGROUND

Human mobility between malaria endemic and malaria-free areas can hinder control and elimination efforts in the Amazon basin, maintaining Plasmodium circulation and introduction to new areas.

METHODS

The analysis begins by estimating the incidence of malaria in areas of interest. Then, the risk of infection as a function of the duration of stay after t₀ was calculated as the number of infected travelers over the number of arrived travelers. Differential equations were employed to estimate the risk of nonimmune travelers acquiring malaria in Amazonian municipalities. Risk was calculated as a result of the force of the infection in terms of local dynamics per time of arrival and duration of visit.

RESULTS

Maximum risk occurred at the peak or at the end of the rainy season and it was nonlinearly (exponentially) correlated with the fraction of infected mosquitoes. Relationship between the risk of malaria and duration of visit was linear and positively correlated. Relationship between the risk of malaria and the time of arrival in the municipality was dependent on local effects of seasonality.

CONCLUSIONS

The risk of nonimmune travelers acquiring malaria is not negligible and can maintain regional circulation of parasites, propagating introductions in areas where malaria has been eliminated.

Malaria outbreak in Riaba district, Bioko Island: lessons learned

At the beginning of 2019, a sudden surge of malaria cases was observed in the district of Riaba, Bioko Island. Between January and April, confirmed malaria cases increased 3.8-fold compared to the same period in 2018. Concurrently, anopheline human biting rate (HBR) increased 2.1-fold. During the outbreak, 82.2% of the district population was tested for malaria with a rapid diagnostic test; 37.2% of those tested had a detectable infection and were treated according to national guidelines. Vector control interventions, including indoor residual spraying and larval source management were scaled-up. After the interventions, the number of confirmed cases decreased by 70% and the overall parasite prevalence in the communities by 43.8%. Observed prevalence in a follow up malaria indicator survey, however, was significantly higher than elsewhere on the island, and higher than in previous years. There was no significant reduction in HBR, which remained high for the rest of the year. The surge was attributed to various factors, chiefly increased rainfall and a large number of anthropogenic anopheline breeding sites created by construction works. This case study highlights the need for sustained vector control interventions and multi-sector participation, particularly in malaria control and elimination settings with persistently high local malaria receptivity.

Genetic polymorphism of Plasmodium falciparum circumsporozoite protein on Bioko Island, Equatorial Guinea and global comparative analysis

BACKGROUND

Plasmodium falciparum circumsporozoite protein (PfCSP) is a potential malaria vaccine candidate, but various polymorphisms of the pfcsp gene among global P. falciparum population become the major barrier to the effectiveness of vaccines. This study aimed to investigate the genetic polymorphisms and natural selection of pfcsp in Bioko and the comparison among global P. falciparum population.

METHODS

From January 2011 to December 2018, 148 blood samples were collected from P. falciparum infected Bioko patients and 96 monoclonal sequences of them were successfully acquired and analysed with 2200 global pfcsp sequences mined from MalariaGEN Pf3k Database and NCBI.

RESULTS

In Bioko, the N-terminus of pfcsp showed limited genetic variations and the numbers of repetitive sequences (NANP/NVDP) were mainly found as 40 (35%) and 41 (34%) in central region. Most polymorphic characters were found in Th2R/Th3R region, where natural selection (p > 0.05) and recombination occurred. The overall pattern of Bioko pfcsp gene had no obvious deviation from African mainland pfcsp (Fst = 0.00878, p < 0.05). The comparative analysis of Bioko and global pfcsp displayed the various mutation patterns and obvious geographic differentiation among populations from four continents (p < 0.05). The global pfcsp C-terminal sequences were clustered into 138 different haplotypes (H_1 to H_138). Only 3.35% of sequences matched 3D7 strain haplotype (H_1).

CONCLUSIONS

The genetic polymorphism phenomena of pfcsp were found universal in Bioko and global isolates and the majority mutations located at T cell epitopes. Global genetic polymorphism and geographical characteristics were recommended to be considered for future improvement of malaria vaccine design.

Characterising malaria connectivity using malaria indicator survey data

Malaria connectivity describes the flow of parasites among transmission sources and sinks within a given landscape. Because of the spatial and temporal scales at which parasites are transported by their hosts, malaria sub-populations are largely defined by mosquito movement and malaria connectivity among them is largely driven by human movement. Characterising malaria connectivity thus requires characterising human travel between areas with differing levels of exposure to malaria. Whilst understanding malaria connectivity is fundamental for optimising interventions, particularly in areas seeking or sustaining elimination, there is a dearth of human movement data required to achieve this goal. Malaria indicator surveys (MIS) are a generally under utilised but potentially rich source of travel data that provide a unique opportunity to study simple associations between malaria infection and human travel in large population samples. This paper shares the experience working with MIS data from Bioko Island that revealed programmatically useful information regarding malaria importation through human travel. Simple additions to MIS questionnaires greatly augmented the level of detail of the travel data, which can be used to characterise human travel patterns and malaria connectivity to assist targeting interventions. It is argued that MIS potentially represent very important and timely sources of travel data that need to be further exploited.

Dynamic Update and Monitoring of AOI Entrance via Spatiotemporal Clustering of Drop-Off Points

This paper proposes a novel method for dynamically extracting and monitoring the entrances of areas of interest (AOIs). Most AOIs in China, such as buildings and communities, are enclosed by walls and are only accessible via one or more entrances. The entrances are not marked on most maps for route planning and navigation in an accurate way. In this work, the extraction scheme of the entrances is based on taxi trajectory data with a 30 s sampling time interval. After fine-grained data cleaning, the position accuracy of the drop-off points extracted from taxi trajectory data is guaranteed. Next, the location of the entrances is extracted, combining the density-based spatial clustering of applications with noise (DBSCAN) with the boundary of the AOI under the constraint of the road network. Based on the above processing, the dynamic update scheme of the entrance is designed. First, a time series analysis is conducted using the clusters of drop-off points within the adjacent AOI, and then, a relative heat index ( R H I ) is applied to detect the recent access status (closed or open) of the entrances. The results show the average accuracy of the current extraction algorithm is improved by 24.3% over the K-means algorithm, and the R H I can reduce the limitation of map symbols in describing the access status. The proposed scheme can, therefore, help optimize the dynamic visualization of the entry symbols in mobile navigation maps, and facilitate human travel behavior and way-finding, which is of great help to sustainable urban development.

Mapping and enumerating houses and households to support malaria control interventions on Bioko Island

BACKGROUND

Housing mapping and household enumeration are essential for the planning, implementation, targeting, and monitoring of malaria control interventions. In many malaria endemic countries, control efforts are hindered by incomplete or non-existent housing cartography and household enumeration. This paper describes the development of a comprehensive mapping and enumeration system to support the Bioko Island Malaria Control Project (BIMCP).

RESULTS

A highly detailed database was developed to include every housing unit on Bioko Island and uniquely enumerate the associated households residing in these houses. First, the island was divided into a virtual, geo-dereferenced grid of 1 × 1 km sequentially numbered map-areas, each of which was in turn subdivided into one hundred, 100 × 100 m sequentially numbered map-sectors. Second, high-resolution satellite imagery was used to sequentially and uniquely identify all housing units within each map-sector. Third, where satellite imagery was not available, global positioning systems (GPS) were used as the basis for uniquely identifying and mapping housing units in a sequential manner. A total of 97,048 housing units were mapped by 2018, 56% of which were concentrated in just 5.2% of Bioko Island's total mapped area. Of these housing units, 70.7% were occupied, thus representing uniquely identified households.

CONCLUSIONS

The housing unit mapping and household enumeration system developed for Bioko Island enabled the BIMCP to more effectively plan, implement, target, and monitor malaria control interventions. Since 2014, the BIMCP has used the unique household identifiers to monitor all household-level interventions, including indoor residual spraying, long-lasting insecticide-treated nets distribution, and annual malaria indicator surveys. The coding system used to create the unique housing unit and household identifiers is highly intuitive and allows quick location of any house within the grid without a GPS. Its flexibility has permitted the BIMCP to easily take into account the rapid and substantial changes in housing infrastructure. Importantly, by utilizing this coding system, an unprecedented quantity and diversity of detailed, geo-referenced demographic and health data have been assembled that have proved highly relevant for informing decision-making both for malaria control and potentially for the wider public health agenda on Bioko Island.