Effect of transmission intensity on hotspots and micro-epidemiology of malaria in sub-Saharan Africa

Malaria transmission heterogeneity in different eco-epidemiological areas of western Kenya: a region-wide observational and risk classification study for adaptive intervention planning

BACKGROUND

Understanding of malaria ecology is a prerequisite for designing locally adapted control strategies in resource-limited settings. The aim of this study was to utilize the spatial heterogeneity in malaria transmission for the designing of adaptive interventions.

METHODS

Field collections of clinical malaria incidence, asymptomatic Plasmodium infection, and malaria vector data were conducted from 108 randomly selected clusters which covered different landscape settings including irrigated farming, seasonal flooding area, lowland dryland farming, and highlands in western Kenya. Spatial heterogeneity of malaria was analyzed and classified into different eco-epidemiological zones.

RESULTS

There was strong heterogeneity and detected hot/cold spots in clinical malaria incidence, Plasmodium prevalence, and vector abundance. The study area was classified into four zones based on clinical malaria incidence, parasite prevalence, vector density, and altitude. The two irrigated zones have either the highest malaria incidence, parasite prevalence, or the highest malaria vector density; the highlands have the lowest vector density and parasite prevalence; and the dryland and flooding area have the average clinical malaria incidence, parasite prevalence and vector density. Different zones have different vector species, species compositions and predominant species. Both indoor and outdoor transmission may have contributed to the malaria transmission in the area. Anopheles gambiae sensu stricto (s.s.), Anopheles arabiensis, Anopheles funestus s.s., and Anopheles leesoni had similar human blood index and malaria parasite sporozoite rate.

CONCLUSION

The multi-transmission-indicator-based eco-epidemiological zone classifications will be helpful for making decisions on locally adapted malaria interventions.

Plasmodium falciparum infection prevalence among children aged 6-59 months from independent DHS and HIV surveys: Nigeria, 2018

Prevalence estimates are critical for malaria programming efforts but generating these from non-malaria surveys is not standard practice. Malaria prevalence estimates for 6-59-month-old Nigerian children were compared between two national household surveys performed simultaneously in 2018: a Demographic and Health Survey (DHS) and the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS). DHS tested via microscopy (n = 8298) and HRP2-based rapid diagnostic test (RDT, n = 11,351), and NAIIS collected dried blood spots (DBS) which were later tested for histidine-rich protein 2 (HRP2) antigen (n = 8029). National Plasmodium falciparum prevalence was 22.6% (95% CI 21.2- 24.1%) via microscopy and 36.2% (34.6- 37.8%) via RDT according to DHS, and HRP2 antigenemia was 38.3% (36.7-39.9%) by NAIIS DBS. Between the two surveys, significant rank-order correlation occurred for state-level malaria prevalence for RDT (Rho = 0.80, p < 0.001) and microscopy (Rho = 0.75, p < 0.001) versus HRP2. RDT versus HRP2 positivity showed 24 states (64.9%) with overlapping 95% confidence intervals from the two independent surveys. P. falciparum prevalence estimates among 6-59-month-olds in Nigeria were highly concordant from two simultaneous, independently conducted household surveys, regardless of malaria test utilized. This provides evidence for the value of post-hoc laboratory HRP2 detection to leverage non-malaria surveys with similar sampling designs to obtain accurate P. falciparum estimates.

Spatiotemporal dynamics of malaria in Zanzibar, 2015-2020

BACKGROUND

Despite high coverage of malaria interventions, malaria elimination in Zanzibar remains elusive, with the annual number of cases increasing gradually over the last 3 years.

OBJECTIVE

The aims of the study were to (1) assess the spatiotemporal dynamics of malaria in Zanzibar between 2015 and 2020 and (2) identify malaria hotspots that would allow Zanzibar to develop an epidemiological stratification for more effective and granular intervention targeting.

METHODS

In this study, we analysed data routinely collected by Zanzibar's Malaria Case Notification (MCN) system. The system collects sociodemographic and epidemiological data from all malaria cases. Cases are passively detected at health facilities (ie, primary index cases) and through case follow-up and reactive case detection (ie, secondary cases). Analyses were performed to identify the spatial heterogeneity of case reporting at shehia (ward) level during transmission seasons.

RESULTS

From 1 January 2015 to 30 April 2020, the MCN system reported 22 686 index cases. Number of cases reported showed a declining trends from 2015 to 2016, followed by an increase from 2017 to 2020. More than 40% of cases had a travel history outside Zanzibar in the month prior to testing positive for malaria. The proportion of followed up index cases was approximately 70% for all years. Out of 387 shehias, 79 (20.4%) were identified as malaria hotspots in any given year; these hotspots reported 52% of all index cases during the study period. Of the 79 hotspot shehias, 12 were hotspots in more than 4 years, that is, considered temporally stable, reporting 14.5% of all index cases.

CONCLUSIONS

Our findings confirm that the scale-up of malaria interventions has greatly reduced malaria transmission in Zanzibar since 2006. Analyses identified hotspots, some of which were stable across multiple years. Malaria efforts should progress from a universal intervention coverage approach to an approach that is more tailored to a select number of hotspot shehias.

Altitude, not potential larval habitat availability, explains pronounced variation in Plasmodium falciparum infection prevalence in the western Kenya highlands

Progress in malaria control has stalled over the recent years. Knowledge on main drivers of transmission explaining small-scale variation in prevalence can inform targeted control measures. We collected finger-prick blood samples from 3061 individuals irrespective of clinical symptoms in 20 clusters in Busia in western Kenya and screened for Plasmodium falciparum parasites using qPCR and microscopy. Clusters spanned an altitude range of 207 meters (1077-1284 m). We mapped potential mosquito larval habitats and determined their number within 250 m of a household and distances to households using ArcMap. Across all clusters, P. falciparum parasites were detected in 49.8% (1524/3061) of individuals by qPCR and 19.5% (596/3061) by microscopy. Across the clusters, prevalence ranged from 26% to 70% by qPCR. Three to 34 larval habitats per cluster and 0-17 habitats within a 250m radius around households were observed. Using a generalized linear mixed effect model (GLMM), a 5% decrease in the odds of getting infected per each 10m increase in altitude was observed, while the number of larval habitats and their proximity to households were not statistically significant predictors for prevalence. Kitchen located indoors, open eaves, a lower level of education of the household head, older age, and being male were significantly associated with higher prevalence. Pronounced variation in prevalence at small scales was observed and needs to be taken into account for malaria surveillance and control. Potential larval habitat frequency had no direct impact on prevalence.

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

Background

Current efforts to estimate the spatially diverse malaria burden in malaria-endemic countries largely involve the use of epidemiological modelling methods for describing temporal and spatial heterogeneity using sparse interpolated prevalence data from periodic cross-sectional surveys. However, more malaria-endemic countries are beginning to consider local routine data for this purpose. Nevertheless, routine information from health facilities (HFs) remains widely under-utilized despite improved data quality, including increased access to diagnostic testing and the adoption of the electronic District Health Information System (DHIS2). This paper describes the process undertaken in mainland Tanzania using routine data to develop a high-resolution, micro-stratification risk map to guide future malaria control efforts.

Methods

Combinations of various routine malariometric indicators collected from 7098 HFs were assembled across 3065 wards of mainland Tanzania for the period 2017–2019. The reported council-level prevalence classification in school children aged 5–16 years (PfPR5–16) was used as a benchmark to define four malaria risk groups. These groups were subsequently used to derive cut-offs for the routine indicators by minimizing misclassifications and maximizing overall agreement. The derived-cutoffs were converted into numbered scores and summed across the three indicators to allocate wards into their overall risk stratum.

Results

Of 3065 wards, 353 were assigned to the very low strata (10.5% of the total ward population), 717 to the low strata (28.6% of the population), 525 to the moderate strata (16.2% of the population), and 1470 to the high strata (39.8% of the population). The resulting micro-stratification revealed malaria risk heterogeneity within 80 councils and identified wards that would benefit from community-level focal interventions, such as community-case management, indoor residual spraying and larviciding.

Conclusion

The micro-stratification approach employed is simple and pragmatic, with potential to be easily adopted by the malaria programme in Tanzania. It makes use of available routine data that are rich in spatial resolution and that can be readily accessed allowing for a stratification of malaria risk below the council level. Such a framework is optimal for supporting evidence-based, decentralized malaria control planning, thereby improving the effectiveness and allocation efficiency of malaria control interventions.

Spatial-temporal pattern of malaria in Burkina Faso from 2013 to 2020

Despite the implementation of different strategies to fight against malaria in Burkina Faso since 2005, it remains today the leading cause of hospitalization and death. Adapting interventions to the spatial and temporal distribution of malaria could help to reduce this burden. This study aims to determine the structure and stability of malaria hotspots in Burkina Faso, with the objective of adapting interventions at small geographical scales.

Data on malaria cases from 2013 to 2020 were acquired at municipalities level. Municipality-wise malaria endemicity levels were mapped through geographical information system (GIS) tools. Spatial statistical analysis using Kulldoff sweeps were carried out to identify malaria hotspots. Then we mapped the monthly malaria risk.

Malaria is endemic in all the municipalities of Burkina Faso. However, two stable main spatial clusters (South-Western and Eastern part of the country) are emerging with seasonal reinforcement.

Interventions targeting the identified clusters could significantly reduce the incidence of malaria in Burkina Faso. This also prompts for further studies to identify the local determinants of this high transmission for the future success of malaria control.

Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016-2017

Malaria control and prevention programs are more efficient and cost-effective when they target hotspots or select the best periods of year to implement interventions. This study aimed to identify the spatial distribution of malaria hotspots at the village level in Diébougou health district, Burkina Faso, and to model the temporal dynamics of malaria cases as a function of meteorological conditions and of the distance between villages and health centres (HCs). Case data for 27 villages were collected in 13 HCs. Meteorological data were obtained through remote sensing. Two synthetic meteorological indicators (SMIs) were created to summarize meteorological variables. Spatial hotspots were detected using the Kulldorf scanning method. A General Additive Model was used to determine the time lag between cases and SMIs and to evaluate the effect of SMIs and distance to HC on the temporal evolution of malaria cases. The multivariate model was fitted with data from the epidemic year to predict the number of cases in the following outbreak. Overall, the incidence rate in the area was 429.13 cases per 1000 person-year with important spatial and temporal heterogeneities. Four spatial hotspots, involving 7 of the 27 villages, were detected, for an incidence rate of 854.02 cases per 1000 person-year. The hotspot with the highest risk (relative risk = 4.06) consisted of a single village, with an incidence rate of 1750.75 cases per 1000 person-years. The multivariate analysis found greater variability in incidence between HCs than between villages linked to the same HC. The time lag that generated the better predictions of cases was 9 weeks for SMI1 (positively correlated with precipitation variables) and 16 weeks for SMI2 (positively correlated with temperature variables. The prediction followed the overall pattern of the time series of reported cases and predicted the onset of the following outbreak with a precision of less than 3 weeks. This analysis of malaria cases in Diébougou health district, Burkina Faso, provides a powerful prospective method for identifying and predicting high-risk areas and high-transmission periods that could be targeted in future malaria control and prevention campaigns.

A global assessment of surveillance methods for dominant malaria vectors

The epidemiology of human malaria differs considerably between and within geographic regions due, in part, to variability in mosquito species behaviours. Recently, the WHO emphasised stratifying interventions using local surveillance data to reduce malaria. The usefulness of vector surveillance is entirely dependent on the biases inherent in the sampling methods deployed to monitor mosquito populations. To understand and interpret mosquito surveillance data, the frequency of use of malaria vector collection methods was analysed from a georeferenced vector dataset (> 10,000 data records), extracted from 875 manuscripts across Africa, the Americas and the Asia-Pacific region. Commonly deployed mosquito collection methods tend to target anticipated vector behaviours in a region to maximise sample size (and by default, ignoring other behaviours). Mosquito collection methods targeting both host-seeking and resting behaviours were seldomly deployed concurrently at the same site. A balanced sampling design using multiple methods would improve the understanding of the range of vector behaviours, leading to improved surveillance and more effective vector control.

Getting to zero: micro-foci of malaria in the Solomon Islands requires stratified control

BACKGROUND

The Solomon Islands has made significant progress in the control of malaria through vector control, access and use of improved diagnostics and therapeutic drugs. As transmission is reduced there is a need to understand variations in transmission risk at the provincial and village levels to stratify control methods.

METHODS

A cross-sectional survey of malaria in humans was conducted in the Solomon Islands during April 2018. Nineteen villages across 4 provinces were included. The presence of Plasmodium species parasites in blood samples was detected using PCR.

RESULTS

Blood samples were analysed from 1,914 participants. The prevalence of DNA of Plasmodium falciparum was 1.2 % (n = 23) and for Plasmodium vivax was 1.5 % (n = 28). 22 % (n = 5/23) of P. falciparum DNA positive participants were febrile and 17 % of P. vivax DNA positive participants (n = 5/28). The prevalence of both P. falciparum and P. vivax was extremely spatially heterogeneous. For P. falciparum, in particular, only 2 small foci of transmission were identified among 19 villages. Plasmodium falciparum infections were uniformly distributed across age groups. Insecticide-treated bed net use the night prior to the survey was reported by 63 % of participants and significantly differed by province.

CONCLUSIONS

Malaria transmission across the Solomon Islands has become increasingly fragmented, affecting fewer villages and provinces. The majority of infections were afebrile suggesting the need for strong active case detection with radical cure with primaquine for P. vivax. Village-level stratification of targeted interventions based on passive and active case detection data could support the progress towards a more cost-effective and successful elimination programme.

Spatial-temporal clustering of malaria using routinely collected health facility data on the Kenyan Coast

BACKGROUND

The over-distributed pattern of malaria transmission has led to attempts to define malaria "hotspots" that could be targeted for purposes of malaria control in Africa. However, few studies have investigated the use of routine health facility data in the more stable, endemic areas of Africa as a low-cost strategy to identify hotspots. Here the objective was to explore the spatial and temporal dynamics of fever positive rapid diagnostic test (RDT) malaria cases routinely collected along the Kenyan Coast.

METHODS

Data on fever positive RDT cases between March 2018 and February 2019 were obtained from patients presenting to six out-patients health-facilities in a rural area of Kilifi County on the Kenyan Coast. To quantify spatial clustering, homestead level geocoded addresses were used as well as aggregated homesteads level data at enumeration zone. Data were sub-divided into quarterly intervals. Kulldorff's spatial scan statistics using Bernoulli probability model was used to detect hotspots of fever positive RDTs across all ages, where cases were febrile individuals with a positive test and controls were individuals with a negative test.

RESULTS

Across 12 months of surveillance, there were nine significant clusters that were identified using the spatial scan statistics among RDT positive fevers. These clusters included 52% of all fever positive RDT cases detected in 29% of the geocoded homesteads in the study area. When the resolution of the data was aggregated at enumeration zone (village) level the hotspots identified were located in the same areas. Only two of the nine hotspots were temporally stable accounting for 2.7% of the homesteads and included 10.8% of all fever positive RDT cases detected.

CONCLUSION

Taking together the temporal instability of spatial hotspots and the relatively modest fraction of the malaria cases that they account for; it would seem inadvisable to re-design the sub-county control strategies around targeting hotspots.

Epidemiological and entomological studies of malaria transmission in Tibati, Adamawa region of Cameroon 6 years following the introduction of long-lasting insecticide nets

BACKGROUND

Malaria remains a serious public health problem in Cameroon. Implementation of control interventions requires prior knowledge of the local epidemiological situation. Here we report the results of epidemiological and entomological surveys carried out in Tibati, Adamawa Region, Cameroon, an area where malaria transmission is seasonal, 6 years after the introduction of long-lasting insecticidal bed nets.

METHODS

Cross-sectional studies were carried out in July 2015 and 2017 in Tibati. Thick blood smears and dried blood spots were collected from asymptomatic and symptomatic individuals in the community and at health centers, respectively, and used for the molecular diagnosis of Plasmodium species. Adult mosquitoes were collected by indoor residual spraying and identified morphologically and molecularly. The infection status of Plasmodium spp. was determined by quantitative PCR, and positivity of PCR-positive samples was confirmed by Sanger sequencing.

RESULTS

Overall malaria prevalence in our study population was 55.0% (752/1367) and Plasmodium falciparum was the most prevalent parasite species (94.3%), followed by P. malariae (17.7%) and P. ovale (0.8%); 92 (12.7%) infections were mixed infections. Infection parameters varied according to clinical status (symptomatic/asymptomatic) and age of the sampled population and the collection sites. Infection prevalence was higher in asymptomatic carriers (60.8%), but asexual and sexual parasite densities were lower. Prevalence and intensity of infection decreased with age in both the symptomatic and asymptomatic groups. Heterogeneity in infections was observed at the neighborhood level, revealing hotspots of transmission. Among the 592 Anopheles mosquitoes collected, 212 (35.8%) were An. gambiae, 172 (29.1%) were An. coluzzii and 208 (35.1%) were An. funestus (s.s.). A total of 26 (4.39%) mosquito specimens were infected by Plasmodium sp. and the three Anopheles mosquitoes transmitted Plasmodium at equal efficiency. Surprisingly, we found an An. coluzzii specimen infected by Plasmodium vivax, which confirms circulation of this species in Cameroon. The positivity of all 26 PCR-positive Plasmodium-infected mosquitoes was successively confirmed by sequencing analysis.

CONCLUSION

Our study presents the baseline malaria parasite burden in Tibati, Adamawa Region, Cameroon. Our results highlight the high malaria endemicity in the area, and hotspots of disease transmission are identified. Parasitological indices suggest low bednet usage and that implementation of control interventions in the area is needed to reduce malaria burden. We also report for the first time a mosquito vector with naturally acquired P. vivax infection in Cameroon.

Quantifying Plasmodium falciparum infections clustering within households to inform household-based intervention strategies for malaria control programs: An observational study and meta-analysis from 41 malaria-endemic countries

BACKGROUND

Reactive malaria strategies are predicated on the assumption that individuals infected with malaria are clustered within households or neighbourhoods. Despite the widespread programmatic implementation of reactive strategies, little empirical evidence exists as to whether such strategies are appropriate and, if so, how they should be most effectively implemented.

METHODS AND FINDINGS

We collated 2 different datasets to assess clustering of malaria infections within households: (i) demographic health survey (DHS) data, integrating household information and patent malaria infection, recent fever, and recent treatment status in children; and (ii) data from cross-sectional and reactive detection studies containing information on the household and malaria infection status (patent and subpatent) of all-aged individuals. Both datasets were used to assess the odds of infections clustering within index households, where index households were defined based on whether they contained infections detectable through one of 3 programmatic strategies: (a) Reactive Case Detection (RACD) classifed by confirmed clinical cases, (b) Mass Screen and Treat (MSAT) classifed by febrile, symptomatic infections, and (c) Mass Test and Treat (MTAT) classifed by infections detectable using routine diagnostics. Data included 59,050 infections in 208,140 children under 7 years old (median age = 2 years, minimum = 2, maximum = 7) by microscopy/rapid diagnostic test (RDT) from 57 DHSs conducted between November 2006 and December 2018 from 23 African countries. Data representing 11,349 infections across all ages (median age = 22 years, minimum = 0.5, maximum = 100) detected by molecular tools in 132,590 individuals in 43 studies published between April 2006 and May 2019 in 20 African, American, Asian, and Middle Eastern countries were obtained from the published literature. Extensive clustering was observed-overall, there was a 20.40 greater (95% credible interval [CrI] 0.35-20.45; P < 0.001) odds of patent infections (according to the DHS data) and 5.13 greater odds (95% CI 3.85-6.84; P < 0.001) of molecularly detected infections (from the published literature) detected within households in which a programmatically detectable infection resides. The strongest degree of clustering identified by polymerase chain reaction (PCR)/ loop mediated isothermal amplification (LAMP) was observed using the MTAT strategy (odds ratio [OR] = 6.79, 95% CI 4.42-10.43) but was not significantly different when compared to MSAT (OR = 5.2, 95% CI 3.22-8.37; P-difference = 0.883) and RACD (OR = 4.08, 95% CI 2.55-6.53; P-difference = 0.29). Across both datasets, clustering became more prominent when transmission was low. However, limitations to our analysis include not accounting for any malaria control interventions in place, malaria seasonality, or the likely heterogeneity of transmission within study sites. Clustering may thus have been underestimated.

CONCLUSIONS

In areas where malaria transmission is peri-domestic, there are programmatic options for identifying households where residual infections are likely to be found. Combining these detection strategies with presumptively treating residents of index households over a sustained time period could contribute to malaria elimination efforts.

VAR2CSA Serology to Detect Plasmodium falciparum Transmission Patterns in Pregnancy

Pregnant women constitute a promising sentinel group for continuous monitoring of malaria transmission. To identify antibody signatures of recent Plasmodium falciparum exposure during pregnancy, we dissected IgG responses against VAR2CSA, the parasite antigen that mediates placental sequestration. We used a multiplex peptide-based suspension array in 2,354 samples from pregnant women from Mozambique, Benin, Kenya, Gabon, Tanzania, and Spain. Two VAR2CSA peptides of limited polymorphism were immunogenic and targeted by IgG responses readily boosted during infection and with estimated half-lives of <2 years. Seroprevalence against these peptides reflected declines and rebounds of transmission in southern Mozambique during 2004–2012, reduced exposure associated with use of preventive measures during pregnancy, and local clusters of transmission that were missed by detection of P. falciparum infections. These data suggest that VAR2CSA serology can provide a useful adjunct for the fine-scale estimation of the malaria burden among pregnant women over time and space.

Programmatic options for monitoring malaria in elimination settings: easy access group surveys to investigate Plasmodium falciparum epidemiology in two regions with differing endemicity in Haiti

BACKGROUND

As in most eliminating countries, malaria transmission is highly focal in Haiti. More granular information, including identifying asymptomatic infections, is needed to inform programmatic efforts, monitor intervention effectiveness, and identify remaining foci. Easy access group (EAG) surveys can supplement routine surveillance with more granular information on malaria in a programmatically tractable way. This study assessed how and which type of venue for EAG surveys can improve understanding malaria epidemiology in two regions with different transmission profiles.

METHODS

EAG surveys were conducted within the departments of Artibonite and Grand'Anse (Haiti), in regions with different levels of transmission intensity. Surveys were conducted in three venue types: primary schools, health facilities, and churches. The sampling approach varied accordingly. Individuals present at the venues at the time of the survey were eligible whether they presented malaria symptoms or not. The participants completed a questionnaire and were tested for Plasmodium falciparum by a highly sensitive rapid diagnostic test (hsRDT). Factors associated with hsRDT positivity were assessed by negative binomial random-effects regression models.

RESULTS

Overall, 11,029 individuals were sampled across 39 venues in Artibonite and 41 in Grand'Anse. The targeted sample size per venue type (2100 in Artibonite and 2500 in Grand'Anse) was reached except for the churches in Artibonite, where some attendees left the venue before they could be approached or enrolled. Refusal rate and drop-out rate were < 1%. In total, 50/6003 (0.8%) and 355/5026 (7.1%) sampled individuals were hsRDT positive in Artibonite and Grand'Anse, respectively. Over half of all infections in both regions were identified at health facilities. Being male and having a current or reported fever in the previous 2 weeks were consistently identified with increased odds of being hsRDT positive.

CONCLUSIONS

Surveys in churches were problematic because of logistical and recruitment issues. However, EAG surveys in health facilities and primary schools provided granular information about malaria burden within two departments in Haiti. The EAG surveys were able to identify residual foci of transmission that were missed by recent national surveys. Non-care seeking and/or asymptomatic malaria infections can be identified in this alternative surveillance tool, facilitating data-driven decision-making for improved targeting of interventions.

Spatio-temporal variation of malaria hotspots in Central Senegal, 2008-2012

Background

In malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. The aim of this work was to describe the spatio-temporal variation of malaria hotspots in central Senegal and to identify the meteorological, environmental, and preventive factors that influence this variation.

Methods

This study analysed the weekly incidence of malaria cases recorded from 2008 to 2012 in 575 villages of central Senegal (total population approximately 500,000) as part of a trial of seasonal malaria chemoprevention (SMC). Data on weekly rainfall and annual vegetation types were obtained for each village through remote sensing. The time series of weekly malaria incidence for the entire study area was divided into periods of high and low transmission using change-point analysis. Malaria hotspots were detected during each transmission period with the SaTScan method. The effects of rainfall, vegetation type, and SMC intervention on the spatio-temporal variation of malaria hotspots were assessed using a General Additive Mixed Model.

Results

The malaria incidence for the entire area varied between 0 and 115.34 cases/100,000 person weeks during the study period. During high transmission periods, the cumulative malaria incidence rate varied between 7.53 and 38.1 cases/100,000 person-weeks, and the number of hotspot villages varied between 62 and 147. During low transmission periods, the cumulative malaria incidence rate varied between 0.83 and 2.73 cases/100,000 person-weeks, and the number of hotspot villages varied between 10 and 43. Villages with SMC were less likely to be hotspots (OR = 0.48, IC95%: 0.33–0.68). The association between rainfall and hotspot status was non-linear and depended on both vegetation type and amount of rainfall. The association between village location in the study area and hotspot status was also shown.

Conclusion

In our study, malaria hotspots varied over space and time according to a combination of meteorological, environmental, and preventive factors. By taking into consideration the environmental and meteorological characteristics common to all hotspots, monitoring of these factors could lead targeted public health interventions at the local level. Moreover, spatial hotspots and foci of malaria persisting during LTPs need to be further addressed.

Trial registration

The data used in this work were obtained from a clinical trial registered on July 10, 2008 at www.clinicaltrials.gov under NCT00712374.

Households or Hotspots? Defining Intervention Targets for Malaria Elimination in Ratanakiri Province, Eastern Cambodia

BACKGROUND

Malaria "hotspots" have been proposed as potential intervention units for targeted malaria elimination. Little is known about hotspot formation and stability in settings outside sub-Saharan Africa.

METHODS

Clustering of Plasmodium infections at the household and hotspot level was assessed over 2 years in 3 villages in eastern Cambodia. Social and spatial autocorrelation statistics were calculated to assess clustering of malaria risk, and logistic regression was used to assess the effect of living in a malaria hotspot compared to living in a malaria-positive household in the first year of the study on risk of malaria infection in the second year.

RESULTS

The crude prevalence of Plasmodium infection was 8.4% in 2016 and 3.6% in 2017. Living in a hotspot in 2016 did not predict Plasmodium risk at the individual or household level in 2017 overall, but living in a Plasmodium-positive household in 2016 strongly predicted living in a Plasmodium-positive household in 2017 (Risk Ratio, 5.00 [95% confidence interval, 2.09-11.96], P < .0001). There was no consistent evidence that malaria risk clustered in groups of socially connected individuals from different households.

CONCLUSIONS

Malaria risk clustered more clearly in households than in hotspots over 2 years. Household-based strategies should be prioritized in malaria elimination programs in this region.

Spatio-temporal dynamics of Plasmodium falciparum transmission within a spatial unit on the Colombian Pacific Coast

As malaria control programmes concentrate their efforts towards malaria elimination a better understanding of malaria transmission patterns at fine spatial resolution units becomes necessary. Defining spatial units that consider transmission heterogeneity, human movement and migration will help to set up achievable malaria elimination milestones and guide the creation of efficient operational administrative control units. Using a combination of genetic and epidemiological data we defined a malaria transmission unit as the area contributing 95% of malaria cases diagnosed at the catchment facility located in the town of Guapi in the South Pacific Coast of Colombia. We provide data showing that P. falciparum malaria transmission is heterogeneous in time and space and analysed, using topological data analysis, the spatial connectivity, at the micro epidemiological level, between parasite populations circulating within the unit. To illustrate the necessity to evaluate the efficacy of malaria control measures within the transmission unit in order to increase the efficiency of the malaria control effort, we provide information on the size of the asymptomatic reservoir, the nature of parasite genotypes associated with drug resistance as well as the frequency of the Pfhrp2/3 deletion associated with false negatives when using Rapid Diagnostic Tests.

Use of real-time multiplex PCR, malaria rapid diagnostic test and microscopy to investigate the prevalence of Plasmodium species among febrile hospital patients in Sierra Leone

Background

Malaria continues to affect over 200 million individuals every year, especially children in Africa. Rapid and sensitive detection and identification of Plasmodium parasites is crucial for treating patients and monitoring of control efforts. Compared to traditional diagnostic methods such as microscopy and rapid diagnostic tests (RDTs), DNA based methods, such as polymerase chain reaction (PCR) offer significantly higher sensitivity, definitive discrimination of Plasmodium species, and detection of mixed infections. While PCR is not currently optimized for routine diagnostics, its role in epidemiological studies is increasing as the world moves closer toward regional and eventually global malaria elimination. This study demonstrates the field use of a novel, ambient temperature-stabilized, multiplexed PCR assay in a small hospital setting in Sierra Leone.

Methods

Blood samples from 534 febrile individuals reporting to a hospital in Bo, Sierra Leone, were tested using three methods: a commercial RDT, microscopy, and a Multiplex Malaria Sample Ready (MMSR) PCR designed to detect a universal malaria marker and species-specific markers for Plasmodium falciparum and Plasmodium vivax. A separate PCR assay was used to identify species of Plasmodium in samples in which MMSR detected malaria, but was unable to identify the species.

Results

MMSR detected the presence of any malaria marker in 50.2% of all tested samples with P. falciparum identified in 48.7% of the samples. Plasmodium vivax was not detected. Testing of MMSR P. falciparum-negative/universal malaria-positive specimens with a panel of species-specific PCRs revealed the presence of Plasmodium malariae (n = 2) and Plasmodium ovale (n = 2). The commercial RDT detected P. falciparum in 24.6% of all samples while microscopy was able to detect malaria in 12.8% of tested specimens.

Conclusions

Wider application of PCR for detection of malaria parasites may help to fill gaps existing as a result of use of microscopy and RDTs. Due to its high sensitivity and specificity, species coverage, room temperature stability and relative low complexity, the MMSR assay may be useful for detection of malaria and epidemiological studies especially in low-resource settings.

Comparing drug regimens for clearance of malaria parasites in asymptomatic adults using PCR in Kilifi County, Kenya: an open-label randomised controlled clinical trial (MalPaC)

Background: To restrict trial endpoints to infections acquired after vaccination in Phase IIb trials of candidate malaria vaccines, participants are treated with anti-malarial drugs to clear existing infections. Anti-malarial drugs with a long half-life may inhibit the acquisition of new infections. This study evaluated the effects of three anti-malarial drug regimens on the clearance of existing infections and acquisition of new infections. Methods: An open-label randomised controlled trial (MalPaC) was conducted between November 2013 and February 2014. Ninety adults were randomised 1:1:1 to receive one of three treatments: atovaquone/proguanil and artesunate (AP+AS); artesunate (AS); or sulphadoxine-pyrimethamine, artesunate, and primaquine (SP+AS+PQ). Parasite monitoring was determined over 84-day follow-up by assessing Plasmodium falciparum positivity by 18s qPCR, live and sexual stage parasites by RT-PCR, and recrudescence of infections by msp2 genotyping. Results: At enrolment, parasite prevalence by qPCR was 44% (40/90, day 0), which fell to 10% (9/90, day 16), then rose to almost the initial rates by day 84 (39%, 35/90). Individuals treated with AS and SP+AS+PQ were more likely to have higher qPCR positive rates compared to participants treated with AP+AS in the immediate post-treatment phase (days 16-28) (OR=7.7 [95%CI 4.6-12.8] p<0.0005 and OR=4.2 [95%CI 2.6-6.8] p<0.0005, respectively). In the immediate post-treatment phase, qPCR positivity was less likely associated with evidence of live parasites and gametocytaemia. Prevalence of “old”, “new” or “undetectable” infections did not differ significantly over time or drug regimen. However, participants on the AP+AS drug regimen were less likely to have parasite infection recrudescence compared to participants treated with AS and SP+AS+PQ. Conclusion: Falciparum DNA remained detectable by PCR post-treatment with incomplete parasite clearance regardless of drug regimen. Though AP+AS drug regimen may also have partially suppressed the acquisition of new infections during post-treatment follow-up. Trial registration: Pan African Clinical Trials Registry, 22nd of August 2013, PACTR201309000625311.

High-resolution micro-epidemiology of parasite spatial and temporal dynamics in a high malaria transmission setting in Kenya

Novel interventions that leverage the heterogeneity of parasite transmission are needed to achieve malaria elimination. To better understand spatial and temporal dynamics of transmission, we applied amplicon next-generation sequencing of two polymorphic gene regions (csp and ama1) to a cohort identified via reactive case detection in a high-transmission setting in western Kenya. From April 2013 to July 2014, we enrolled 442 symptomatic children with malaria, 442 matched controls, and all household members of both groups. Here, we evaluate genetic similarity between infected individuals using three indices: sharing of parasite haplotypes on binary and proportional scales and the L1 norm. Symptomatic children more commonly share haplotypes with their own household members. Furthermore, we observe robust temporal structuring of parasite genetic similarity and identify the unique molecular signature of an outbreak. These findings of both micro- and macro-scale organization of parasite populations might be harnessed to inform next-generation malaria control measures.

Here, Nelson et al. use amplicon next-generation sequencing of two P. falciparum polymorphic gene regions to investigate the genetic similarity of parasite populations across time and space in a pediatric cohort in Kenya. They identify both micro- and macro-scale structuring of malaria parasites in this high-transmission setting, which could inform future intervention strategies.

Molecular epidemiology of residual Plasmodium vivax transmission in a paediatric cohort in Solomon Islands

Background

Following the scale-up of intervention efforts, malaria burden has decreased dramatically in Solomon Islands (SI). Submicroscopic and asymptomatic Plasmodium vivax infections are now the major challenge for malaria elimination in this country. Since children have higher risk of contracting malaria, this study investigated the dynamics of Plasmodium spp. infections among children including the associated risk factors of residual P. vivax burden.

Methods

An observational cohort study was conducted among 860 children aged 0.5–12 years in Ngella (Central Islands Province, SI). Children were monitored by active and passive surveillances for Plasmodium spp. infections and illness. Parasites were detected by quantitative real-time PCR (qPCR) and genotyped. Comprehensive statistical analyses of P. vivax infection prevalence, molecular force of blood stage infection (_molFOB) and infection density were conducted.

Results

Plasmodium vivax infections were common (overall prevalence: 11.9%), whereas Plasmodium falciparum infections were rare (0.3%) but persistent. Although children acquire an average of 1.1 genetically distinct P. vivax blood-stage infections per year, there was significant geographic heterogeneity in the risks of P. vivax infections across Ngella (prevalence: 1.2–47.4%, p < 0.01; _molFOB: 0.05–4.6/year, p < 0.01). Malaria incidence was low (IR: 0.05 episodes/year-at-risk). Age and measures of high exposure were the key risk factors for P. vivax infections and disease. Malaria incidence and infection density decreased with age, indicating significant acquisition of immunity. G6PD deficient children (10.8%) that did not receive primaquine treatment had a significantly higher prevalence (_aOR: 1.77, p = 0.01) and increased risk of acquiring new bloodstage infections (_molFOB _aIRR: 1.51, p = 0.03), underscoring the importance of anti-relapse treatment.

Conclusion

Residual malaria transmission in Ngella exhibits strong heterogeneity and is characterized by a high proportion of submicroscopic and asymptomatic P. vivax infections, alongside sporadic P. falciparum infections. Implementing an appropriate primaquine treatment policy to prevent P. vivax relapses and specific targeting of control interventions to high risk areas will be required to accelerate ongoing control and elimination activities.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2727-9) contains supplementary material, which is available to authorized users.

Complexity-Based Spatial Hierarchical Clustering for Malaria Prediction

Targeted intervention and resource allocation are essential in effective control of infectious diseases, particularly those like malaria that tend to occur in remote areas. Disease prediction models can help support targeted intervention, particularly if they have fine spatial resolution. But, choosing an appropriate resolution is a difficult problem since choice of spatial scale can have a significant impact on accuracy of predictive models. In this paper, we introduce a new approach to spatial clustering for disease prediction we call complexity-based spatial hierarchical clustering. The technique seeks to find spatially compact clusters that have time series that can be well characterized by models of low complexity. We evaluate our approach with 2 years of malaria case data from Tak Province in northern Thailand. We show that the technique's use of reduction in Akaike information criterion (AIC) and Bayesian information criterion (BIC) as clustering criteria leads to rapid improvement in predictability and significantly better predictability than clustering based only on minimizing spatial intra-cluster distance for the entire range of cluster sizes over a variety of predictive models and prediction horizons.

Detection of foci of residual malaria transmission through reactive case detection in Ethiopia

Background

Sub-microscopic and asymptomatic infections could be bottlenecks to malaria elimination efforts in Ethiopia. This study determined the prevalence of malaria, and individual and household-level factors associated with Plasmodium infections obtained following detection of index cases in health facilities in Jimma Zone.

Methods

Index malaria cases were passively detected and tracked in health facilities from June to November 2016. Moreover, family members of the index houses and neighbours located within approximately 200 m from the index houses were also screened for malaria.

Results

A total of 39 index cases initiated the reactive case detection of 726 individuals in 116 households. Overall, the prevalence of malaria using microscopy and PCR was 4.0% and 8.96%, respectively. Seventeen (43.6%) of the index cases were from Doyo Yaya kebele, where parasite prevalence was higher. The majority of the malaria cases (90.74%) were asymptomatic. Fever (AOR = 12.68, 95% CI 3.34–48.18) and history of malaria in the preceding 1 year (AOR = 3.62, 95% CI 1.77–7.38) were significant individual-level factors associated with detection of Plasmodium infection. Moreover, living in index house (AOR = 2.22, 95% CI 1.16–4.27), house with eave (AOR = 2.28, 95% CI 1.14–4.55), area of residence (AOR = 6.81, 95% CI 2.49–18.63) and family size (AOR = 3.35, 95% CI 1.53–7.33) were main household-level predictors for residual malaria transmission.

Conclusion

The number of index cases per kebele may enhance RACD efforts to detect additional malaria cases in low transmission settings. Asymptomatic and sub-microscopic infections were high in the study area, which need new or improved surveillance tools for malaria elimination efforts.

Do hotspots fuel malaria transmission: a village-scale spatio-temporal analysis of a 2-year cohort study in The Gambia

BACKGROUND

Despite the biological plausibility of hotspots fueling malaria transmission, the evidence to support this concept has been mixed. If transmission spreads from high burden to low burden households in a consistent manner, then this could have important implications for control and elimination program development.

METHODS

Data from a longitudinal cohort in The Gambia was analyzed. All consenting individuals residing in 12 villages across the country were sampled monthly from June (dry season) to December 2013 (wet season), in April 2014 (mid dry season), and monthly from June to December 2014. A study nurse stationed within each village recorded passively detected malaria episodes between visits. Plasmodium falciparum infections were determined by polymerase chain reaction and analyzed using a geostatistical model.

RESULTS

Household-level observed monthly incidence ranged from 0 to 0.50 infection per person (interquartile range = 0.02-0.10) across the sampling months, and high burden households exist across all study villages. There was limited evidence of a spatio-temporal pattern at the monthly timescale irrespective of transmission intensity. Within-household transmission was the most plausible hypothesis examined to explain the observed heterogeneity in infections.

CONCLUSIONS

Within-village malaria transmission patterns are concentrated in a small proportion of high burden households, but patterns are stochastic regardless of endemicity. Our findings support the notion of transmission occurring at the household and village scales but not the use of a targeted approach to interrupt spreading of infections from high to low burden areas within villages in this setting.

Mapping the stability of malaria hotspots in Bangladesh from 2013 to 2016

BACKGROUND

Malaria claims hundreds of thousands of lives each year, most of them children. A "malaria-free world" is the World Health Organization's vision, but elimination from the southeast Asian Region is hampered by factors including anti-malarial resistance and systematic underreporting. Malaria is a significant public health problem in Bangladesh and while there have been recent gains in control, there is large spatial and temporal heterogeneity in the disease burden. This study aims to determine the pattern and stability of malaria hotspots in Bangladesh with the end goal of informing intervention planning for elimination.

RESULTS

Malaria in Bangladesh exhibited highly seasonal, hypoendemic transmission in geographic hotspots, which remained conserved over time. The southeast areas of the Chittagong Hill Tracts were identified as malaria hotspots for all 4 years examined. Similarly, areas in Sunamganj and Netrakona districts in the Northeast were hotspots for 2013-2016. Highly stable hotspots from 1 year predicted the following year's hotspot locations in the southeast of Bangladesh. Hotspots did not appear to act as sources of spread with no evidence of consistent patterns of contiguous spread or recession of hotspots as high or low transmission seasons progressed.

CONCLUSIONS

Areas were identified with temporal and spatial clustering of high malaria incidence in Bangladesh. Further studies are required to understand the vector, sociodemographic and disease dynamics within these hotspots. Given the low caseloads occurring in the low transmission seasons, and the conserved nature of malaria hotspots, directing resources towards these areas may be an efficient way to achieve malaria elimination in Bangladesh.

Spatio-temporal dynamic of malaria in Ouagadougou, Burkina Faso, 2011-2015

Background

Given the scarcity of resources in developing countries, malaria treatment requires new strategies that target specific populations, time periods and geographical areas. While the spatial pattern of malaria transmission is known to vary depending on local conditions, its temporal evolution has yet to be evaluated. The aim of this study was to determine the spatio-temporal dynamic of malaria in the central region of Burkina Faso, taking into account meteorological factors.

Methods

Drawing on national databases, 101 health areas were studied from 2011 to 2015, together with weekly meteorological data (temperature, number of rain events, rainfall, humidity, wind speed). Meteorological factors were investigated using a principal component analysis (PCA) to reduce dimensions and avoid collinearities. The Box–Jenkins ARIMA model was used to test the stationarity of the time series. The impact of meteorological factors on malaria incidence was measured with a general additive model. A change-point analysis was performed to detect malaria transmission periods. For each transmission period, malaria incidence was mapped and hotspots were identified using spatial cluster detection.

Results

Malaria incidence never went below 13.7 cases/10,000 person-weeks. The first and second PCA components (constituted by rain/humidity and temperatures, respectively) were correlated with malaria incidence with a lag of 2 weeks. The impact of temperature was significantly non-linear: malaria incidence increased with temperature but declined sharply with high temperature. A significant positive linear trend was found for the entire time period. Three transmission periods were detected: low (16.8–29.9 cases/10,000 person-weeks), high (51.7–84.8 cases/10,000 person-weeks), and intermediate (26.7–32.2 cases/10,000 person-weeks). The location of clusters identified as high risk varied little across transmission periods.

Conclusion

This study highlighted the spatial variability and relative temporal stability of malaria incidence around the capital Ouagadougou, in the central region of Burkina Faso. Despite increasing efforts in fighting the disease, malaria incidence remained high and increased over the period of study. Hotspots, particularly those detected for low transmission periods, should be investigated further to uncover the local environmental and behavioural factors of transmission, and hence to allow for the development of better targeted control strategies.

Electronic supplementary material

The online version of this article (10.1186/s12936-018-2280-y) contains supplementary material, which is available to authorized users.

What goes around comes around: modeling malaria transmission from humans back to mosquitos

Malaria, caused by mosquito-transmitted Plasmodium parasites, continues to take a major toll on global health. The development of drugs and vaccines that reduce malaria transmission from humans back to mosquitos could contribute to the control and eventual eradication of malaria, but research models for the early clinical evaluation of candidate interventions are lacking. In this issue of the JCI, Collins and colleagues report the successful transmission of Plasmodium falciparum parasites from humans to mosquitoes during controlled human malaria infection, thus providing a potential tool to accelerate the development of much needed transmission-blocking drugs and vaccines.