The Impact of Hotspot-Targeted Interventions on Malaria Transmission in Rachuonyo South District in the Western Kenyan Highlands: A Cluster-Randomized Controlled Trial

Microheterogeneity of Transmission Shapes Submicroscopic Malaria Carriage in Coastal Tanzania

BACKGROUND

Asymptomatic carriage of malaria parasites persists even as malaria transmission declines. Low-density infections are often submicroscopic, not detected with rapid diagnostic tests (RDTs) or microscopy but detectable by polymerase chain reaction (PCR).

METHODS

To characterize submicroscopic Plasmodium falciparum carriage in an area of declining malaria transmission, asymptomatic persons >5 years of age in rural Bagamoyo District, Tanzania, were screened using RDT, microscopy, and PCR. We investigated the size of the submicroscopic reservoir of infection across villages, determined factors associated with submicroscopic carriage, and assessed the natural history of submicroscopic malaria over 4 weeks.

RESULTS

Among 6076 participants, P. falciparum prevalences by RDT, microscopy, and PCR were 9%, 9%, and 28%, respectively, with roughly two-thirds of PCR-positive individuals harboring submicroscopic infection. Adult status, female sex, dry season months, screened windows, and bed net use were associated with submicroscopic carriage. Among 15 villages encompassing 80% of participants, the proportion of submicroscopic carriers increased with decreasing village-level malaria prevalence. Over 4 weeks, 23% of submicroscopic carriers (61 of 266) became RDT positive, with half exhibiting symptoms, while half (133 of 266) were no longer parasitemic at the end of 4 weeks. Progression to RDT-positive patent malaria occurred more frequently in villages with higher malaria prevalence.

CONCLUSIONS

Microheterogeneity in transmission observed at the village level appears to affect both the size of the submicroscopic reservoir and the likelihood of submicroscopic carriers developing patent malaria in coastal Tanzania.

Mapping malaria transmission foci in Northeast Thailand from 2011 to 2021: approaching elimination in a hypoendemic area

BACKGROUND

Thailand is approaching local elimination of malaria in the eastern provinces. It has successfully reduced the number of cases over the past decade, but there are persistent transmission hot spots in and around forests. This study aimed to use data from the malaria surveillance system to describe the spatiotemporal trends of malaria in Northeast Thailand and fine-scale patterns in locally transmitted cases between 2011 and 2021.

METHODS

Case data was stratified based on likely location of infection and parasite species. Annual Parasite Index per 1000 population (API) was calculated for different categories. Time series decomposition was performed to identify trends and seasonal patterns. Statistically significant clusters of high (hot spots) and low (cold spots) API were identified using the Getis-Ord Gi* statistic. The stability of those hot spots and the absolute change in the proportion of API density from baseline were compared by case type.

RESULTS

The total number of confirmed cases experienced a non-linear decline by 96.6%, from 1061 in 2011 to 36 in 2021. There has been a decline in both Plasmodium vivax and Plasmodium falciparum case numbers, with only four confirmed P. falciparum cases over the last two years-a 98.89% drop from 180 in 2011. API was generally higher in Si Sa Ket province, which had peaks every 2-3 years. There was a large outbreak in Ubon Ratchathani in 2014-2016 which had a high proportion of P. falciparum reported. The proportion of cases classified increased over the study period, and the proportion of cases classed as indigenous to the village of residence increased from 0.2% to 33.3%. There were stable hot spots of indigenous and imported cases in the south of Si Sa Ket and southeast of Ubon Ratchathani. Plasmodium vivax hot spots were observed into recent years, while those of P. falciparum decreased to zero in Ubon in 2020 and emerged in the eastern part in 2021, the same year that P. falciparum hot spots in Si Sa Ket reached zero.

CONCLUSIONS

There has been a large, non-linear decline in the number of malaria cases reported and an increasing proportion of cases are classed as indigenous to the patient's village of residence. Stable hot spots of ongoing transmission in the forested border areas were identified, with transmission likely persisting because of remote location and high-risk forest-going behaviours. Future efforts should include cross-border collaboration and continued targeting of high-risk behaviours to reduce the risk of imported cases seeding local transmission.

Extension of efficacy range for targeted malaria-elimination interventions due to spillover effects

Malaria-elimination interventions aim to extinguish hotspots and prevent transmission to nearby areas. Here, we re-analyzed a cluster-randomized trial of reactive, focal interventions (chemoprevention using artemether-lumefantrine and/or indoor residual spraying with pirimiphos-methyl) delivered within 500 m of confirmed malaria index cases in Namibia to measure direct effects (among intervention recipients within 500 m) and spillover effects (among non-intervention recipients within 3 km) on incidence, prevalence and seroprevalence. There was no or weak evidence of direct effects, but the sample size of intervention recipients was small, limiting statistical power. There was the strongest evidence of spillover effects of combined chemoprevention and indoor residual spraying. Among non-recipients within 1 km of index cases, the combined intervention reduced malaria incidence by 43% (95% confidence interval, 20-59%). In analyses among non-recipients within 3 km of interventions, the combined intervention reduced infection prevalence by 79% (6-95%) and seroprevalence, which captures recent infections and has higher statistical power, by 34% (20-45%). Accounting for spillover effects increased the cost-effectiveness of the combined intervention by 42%. Targeting hotspots with combined chemoprevention and vector-control interventions can indirectly benefit non-recipients up to 3 km away.

Strong isolation by distance and evidence of population microstructure reflect ongoing Plasmodium falciparum transmission in Zanzibar

Background

The Zanzibar archipelago of Tanzania has become a low-transmission area for Plasmodium falciparum. Despite being considered an area of pre-elimination for years, achieving elimination has been difficult, likely due to a combination of imported infections from mainland Tanzania and continued local transmission.

Methods

To shed light on these sources of transmission, we applied highly multiplexed genotyping utilizing molecular inversion probes to characterize the genetic relatedness of 282 P. falciparum isolates collected across Zanzibar and in Bagamoyo district on the coastal mainland from 2016 to 2018.

Results

Overall, parasite populations on the coastal mainland and Zanzibar archipelago remain highly related. However, parasite isolates from Zanzibar exhibit population microstructure due to the rapid decay of parasite relatedness over very short distances. This, along with highly related pairs within shehias, suggests ongoing low-level local transmission. We also identified highly related parasites across shehias that reflect human mobility on the main island of Unguja and identified a cluster of highly related parasites, suggestive of an outbreak, in the Micheweni district on Pemba island. Parasites in asymptomatic infections demonstrated higher complexity of infection than those in symptomatic infections, but have similar core genomes.

Conclusions

Our data support importation as a main source of genetic diversity and contribution to the parasite population in Zanzibar, but they also show local outbreak clusters where targeted interventions are essential to block local transmission. These results highlight the need for preventive measures against imported malaria and enhanced control measures in areas that remain receptive to malaria reemergence due to susceptible hosts and competent vectors.

Funding

This research was funded by the National Institutes of Health, grants R01AI121558, R01AI137395, R01AI155730, F30AI143172, and K24AI134990. Funding was also contributed from the Swedish Research Council, Erling-Persson Family Foundation, and the Yang Fund. RV acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 program supported by the European Union. RV also acknowledges funding by Community Jameel.

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.

Understanding the spread of infectious diseases in edge areas of hotspots: dengue epidemics in tropical metropolitan regions

Identifying clusters or hotspots from disease maps is critical in research and practice. Hotspots have been shown to have a higher potential for transmission risk and may be the source of infections, making them a priority for controlling epidemics. However, the role of edge areas of hotspots in disease transmission remains unclear. This study aims to investigate the role of edge areas in disease transmission by examining whether disease incidence rate growth is higher in the edges of disease hotspots during outbreaks. Our data is based on the three most severe dengue epidemic years in Kaohsiung city, Taiwan, from 1998 to 2020. We employed conditional autoregressive (CAR) models and Bayesian areal Wombling methods to identify significant edge areas of hotspots based on the extent of risk difference between adjacent areas. The difference-in-difference (DID) estimator in spatial panel models measures the growth rate of risk by comparing the incidence rate between two groups (hotspots and edge areas) over two time periods. Our results show that in years characterized by exceptionally large-scale outbreaks, the edge areas of hotspots have a more significant increase in disease risk than hotspots, leading to a higher risk of disease transmission and potential disease foci. This finding explains the geographic diffusion mechanism of epidemics, a pattern mixed with expansion and relocation, indicating that the edge areas play an essential role. The study highlights the importance of considering edge areas of hotspots in disease transmission. Furthermore, it provides valuable insights for policymakers and health authorities in designing effective interventions to control large-scale disease outbreaks.

Targeted malaria elimination interventions reduce Plasmodium falciparum infections up to 3 kilometers away

Malaria elimination interventions in low-transmission settings aim to extinguish hot spots and prevent transmission to nearby areas. In malaria elimination settings, the World Health Organization recommends reactive, focal interventions targeted to the area near malaria cases shortly after they are detected. A key question is whether these interventions reduce transmission to nearby uninfected or asymptomatic individuals who did not receive interventions. Here, we measured direct effects (among intervention recipients) and spillover effects (among non-recipients) of reactive, focal interventions delivered within 500m of confirmed malaria index cases in a cluster-randomized trial in Namibia. The trial delivered malaria chemoprevention (artemether lumefantrine) and vector control (indoor residual spraying with Actellic) separately and in combination using a factorial design. We compared incidence, infection prevalence, and seroprevalence between study arms among intervention recipients (direct effects) and non-recipients (spillover effects) up to 3 km away from index cases. We calculated incremental cost-effectiveness ratios accounting for spillover effects. The combined chemoprevention and vector control intervention produced direct effects and spillover effects. In the primary analysis among non-recipients within 1 km from index cases, the combined intervention reduced malaria incidence by 43% (95% CI 20%, 59%). In secondary analyses among non-recipients 500m-3 km from interventions, the combined intervention reduced infection by 79% (6%, 95%) and seroprevalence 34% (20%, 45%). Accounting for spillover effects increased the cost-effectiveness of the combined intervention by 37%. Our findings provide the first evidence that targeting hot spots with combined chemoprevention and vector control interventions can indirectly benefit non-recipients up to 3 km away.

Testing and treatment for malaria elimination: a systematic review

BACKGROUND

Global interest in malaria elimination has prompted research on active test and treat (TaT) strategies.

METHODS

A systematic review and meta-analysis were conducted to assess the effectiveness of TaT strategies to reduce malaria transmission.

RESULTS

A total of 72 empirical research and 24 modelling studies were identified, mainly focused on proactive mass TaT (MTaT) and reactive case detection (RACD) in higher and lower transmission settings, respectively. Ten intervention studies compared MTaT to no MTaT and the evidence for impact on malaria incidence was weak. No intervention studies compared RACD to no RACD. Compared to passive case detection (PCD) alone, PCD + RACD using standard diagnostics increased infection detection 52.7% and 11.3% in low and very low transmission settings, respectively. Using molecular methods increased this detection of infections by 1.4- and 1.1-fold, respectively.

CONCLUSION

Results suggest MTaT is not effective for reducing transmission. By increasing case detection, surveillance data provided by RACD may indirectly reduce transmission by informing coordinated responses of intervention targeting.

Impact of mass distribution of long-lasting insecticide nets on the incidence of malaria in Lomami, Democratic Republic of Congo: a study based on electronic health record data (2018 - 2019)

Introduction

holoendemic, malaria remains one of the major public health problems in Lomami Province in the Democratic Republic of Congo (DRC). To fight against it, a free mass distribution of long-lasting insecticide nets (LLINs) was organized in July 2019 throughout the province. The present study aimed to assess the incidence of malaria and its impact on anaemia of children from 0 to 59 months in this region before and after this intervention.

Methods

we had conducted a retrospective observational study from June to December 2018 and June to December 2019. The data were collected on District Health Information System version two (DHIS2) and analyzed with T-tests to compare the incidence rates before (second semester 2018) and after the distribution of LLINs (second semester 2019).

Results

the evolution of malaria cases immediately dropped after the distribution campaign. The incidence rates per 1,000 inhabitants in 2018 and 2019 were 106 and 107 respectively in the general population; 302 versus 305 in children aged 0 to 59 months and 219 versus 209 in pregnant women. The differences in incidence were not statistically significant with p values 0.497, 0.4602, and 0.3097 respectively. However, it was observed that the decrease in malaria cases led to a decrease in anaemia cases in general.

Conclusion

the LLIN distribution campaign did not decrease the incidence of malaria. The synergy of preventive interventions to reduce the incidence of malaria remains key.

Integrated malaria prevention in low- and middle-income countries: a systematic review

BACKGROUND

As many countries aim to eliminate malaria, use of comprehensive approaches targeting the mosquito vector and environment are needed. Integrated malaria prevention advocates the use of several malaria prevention measures holistically at households and in the community. The aim of this systematic review was to collate and summarize the impact of integrated malaria prevention in low- and middle-income countries on malaria burden.

METHODS

Literature on integrated malaria prevention, defined as the use of two or more malaria prevention methods holistically, was searched from 1st January 2001 to 31st July 2021. The primary outcome variables were malaria incidence and prevalence, while the secondary outcome measures were human biting and entomological inoculation rates, and mosquito mortality.

RESULTS

A total of 10,931 studies were identified by the search strategy. After screening, 57 articles were included in the review. Studies included cluster randomized controlled trials, longitudinal studies, programme evaluations, experimental hut/houses, and field trials. Various interventions were used, mainly combinations of two or three malaria prevention methods including insecticide-treated nets (ITNs), indoor residual spraying (IRS), topical repellents, insecticide sprays, microbial larvicides, and house improvements including screening, insecticide-treated wall hangings, and screening of eaves. The most common methods used in integrated malaria prevention were ITNs and IRS, followed by ITNs and topical repellents. There was reduced incidence and prevalence of malaria when multiple malaria prevention methods were used compared to single methods. Mosquito human biting and entomological inoculation rates were significantly reduced, and mosquito mortality increased in use of multiple methods compared to single interventions. However, a few studies showed mixed results or no benefits of using multiple methods to prevent malaria.

CONCLUSION

Use of multiple malaria prevention methods was effective in reducing malaria infection and mosquito density in comparison with single methods. Results from this systematic review can be used to inform future research, practice, policy and programming for malaria control in endemic countries.

Spatio-temporal monitoring of health facility-level malaria trends in Zambia and adaptive scaling for operational intervention

Background

The spatial and temporal variability inherent in malaria transmission within countries implies that targeted interventions for malaria control in high-burden settings and subnational elimination are a practical necessity. Identifying the spatio-temporal incidence, risk, and trends at different administrative geographies within malaria-endemic countries and monitoring them in near real-time as change occurs is crucial for developing and introducing cost-effective, subnational control and elimination intervention strategies.

Methods

This study developed intelligent data analytics incorporating Bayesian trend and spatio-temporal Integrated Laplace Approximation models to analyse high-burden over 32 million reported malaria cases from 1743 health facilities in Zambia between 2009 and 2015.

Results

The results show that at least 5.4 million people live in catchment areas with increasing trends of malaria, covering over 47% of all health facilities, while 5.7 million people live in areas with a declining trend (95% CI), covering 27% of health facilities. A two-scale spatio-temporal trend comparison identified significant differences between health facilities and higher-level districts, and the pattern observed in the southeastern region of Zambia provides the first evidence of the impact of recently implemented localised interventions.

Conclusions

The results support our recommendation for an adaptive scaling approach when implementing national malaria monitoring, control and elimination strategies and a particular need for stratified subnational approaches targeting high-burden regions with increasing disease trends. Strong clusters along borders with highly endemic countries in the north and south of Zambia underscore the need for coordinated cross-border malaria initiatives and strategies.

Malaria is an infectious disease that is widespread in many African countries. Malaria transmission within a country can vary between regions, so tailored interventions for malaria control and elimination targeted to different regions are necessary. To achieve this, it is important to measure and monitor the frequency of malaria infections, its risk, and trends at different geographic administrative scales. This study analysed over 32 million reported malaria cases from 1743 health facilities in Zambia between 2009 and 2015. The results showed an increasing national trend in malaria risk and malaria infection frequency and identified differences between health facility and district trends. These findings support a flexible approach when implementing and expanding national malaria monitoring, control and elimination strategies, especially in areas bordering countries where malaria is widespread, cross-border movement is common, and cross-border initiatives could be beneficial.

Lubinda et al. analyse over 32 million health-facility reported malaria cases in Zambia (2009–15) to examine spatially-structured temporal trends. They observe overall increasing trends in risk and rates and highlight the potential benefits of using an adaptive scaling approach in national malaria strategies, and a need for cross-border initiatives.

Impact of the malaria comprehensive case management programme in Odisha, India

Background

The Comprehensive Case Management Project (CCMP), was a collaborative implementation research initiative to strengthen malaria early detection and complete treatment in Odisha State, India.

Methods

A two-arm quasi-experimental design was deployed across four districts in Odisha, representing a range of malaria endemicity: Bolangir (low), Dhenkanal (moderate), Angul (high), and Kandhamal (hyper). In each district, a control block received routine malaria control measures, whereas a CCMP block received a range of interventions to intensify surveillance, diagnosis, and case management. Impact was evaluated by difference-in-difference (DID) analysis and interrupted time-series (ITS) analysis of monthly blood examination rate (MBER) and monthly parasite index (MPI) over three phases: phase 1 pre-CCMP (2009–2012) phase 2 CCMP intervention (2013–2015), and phase 3 post-CCMP (2016–2017).

Results

During CCMP implementation, adjusting for control blocks, DID and ITS analysis indicated a 25% increase in MBER and a 96% increase in MPI, followed by a –47% decline in MPI post-CCMP, though MBER was maintained. Level changes in MPI between phases 1 and 2 were most marked in Dhenkanal and Angul with increases of 976% and 287%, respectively, but declines in Bolangir (−57%) and Kandhamal (−22%). Between phase 2 and phase 3, despite the MBER remaining relatively constant, substantial decreases in MPI were observed in Dhenkanal (−78%), and Angul (−59%), with a more modest decline in Bolangir (−13%), and an increase in Kandhamal (14%).

Conclusions

Overall, CCMP improved malaria early detection and treatment through the enhancement of the existing network of malaria services which positively impacted case incidence in three districts. In Kandhamal, which is hyperendemic, the impact was not evident. However, in Dhenkanal and Angul, areas of moderate-to-high malaria endemicity, CCMP interventions precipitated a dramatic increase in case detection and a subsequent decline in malaria incidence, particularly in previously difficult-to-reach communities.

Determining target populations for leprosy prophylactic interventions: a hotspot analysis in Indonesia

Background

Leprosy incidence remained at around 200,000 new cases globally for the last decade. Current strategies to reduce the number of new patients include early detection and providing post-exposure prophylaxis (PEP) to at-risk populations. Because leprosy is distributed unevenly, it is crucial to identify high-risk clusters of leprosy cases for targeting interventions. Geographic Information Systems (GIS) methodology can be used to optimize leprosy control activities by identifying clustering of leprosy cases and determining optimal target populations for PEP.

Methods

The geolocations of leprosy cases registered from 2014 to 2018 in Pasuruan and Pamekasan (Indonesia) were collected and tested for spatial autocorrelation with the Moran’s I statistic. We did a hotspot analysis using the Heatmap tool of QGIS to identify clusters of leprosy cases in both areas. Fifteen cluster settings were compared, varying the heatmap radius (i.e., 500 m, 1000 m, 1500 m, 2000 m, or 2500 m) and the density of clustering (low, moderate, and high). For each cluster setting, we calculated the number of cases in clusters, the size of the cluster (km²), and the total population targeted for PEP under various strategies.

Results

The distribution of cases was more focused in Pasuruan (Moran’s I = 0.44) than in Pamekasan (0.27). The proportion of total cases within identified clusters increased with heatmap radius and ranged from 3% to almost 100% in both areas. The proportion of the population in clusters targeted for PEP decreased with heatmap radius from > 100% to 5% in high and from 88 to 3% in moderate and low density clusters. We have developed an example of a practical guideline to determine optimal cluster settings based on a given PEP strategy, distribution of cases, resources available, and proportion of population targeted for PEP.

Conclusion

Policy and operational decisions related to leprosy control programs can be guided by a hotspot analysis which aid in identifying high-risk clusters and estimating the number of people targeted for prophylactic interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07103-0.

A threshold-free approach with age-dependency for estimating malaria seroprevalence

Background

In malaria serology analysis, the standard approach to obtain seroprevalence, i.e the proportion of seropositive individuals in a population, is based on a threshold which is used to classify individuals as seropositive or seronegative. The choice of this threshold is often arbitrary and is based on methods that ignore the age-dependency of the antibody distribution.

Methods

Using cross-sectional antibody data from the Western Kenyan Highlands, this paper introduces a novel approach that has three main advantages over the current threshold-based approach: it avoids the use of thresholds; it accounts for the age dependency of malaria antibodies; and it allows us to propagate the uncertainty from the classification of individuals into seropositive and seronegative when estimating seroprevalence. The reversible catalytic model is used as an example for illustrating how to propagate this uncertainty into the parameter estimates of the model.

Results

This paper finds that accounting for age-dependency leads to a better fit to the data than the standard approach which uses a single threshold across all ages. Additionally, the paper also finds that the proposed threshold-free approach is more robust against the selection of different age-groups when estimating seroprevalence.

Conclusion

The novel threshold-free approach presented in this paper provides a statistically principled and more objective approach to estimating malaria seroprevalence. The introduced statistical framework also provides a means to compare results across studies which may use different age ranges for the estimation of seroprevalence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-04022-4.

Identifying Plasmodium falciparum transmission patterns through parasite prevalence and entomological inoculation rate

Background

Monitoring malaria transmission is a critical component of efforts to achieve targets for elimination and eradication. Two commonly monitored metrics of transmission intensity are parasite prevalence (PR) and the entomological inoculation rate (EIR). Comparing the spatial and temporal variations in the PR and EIR of a given geographical region and modelling the relationship between the two metrics may provide a fuller picture of the malaria epidemiology of the region to inform control activities.

Methods

Using geostatistical methods, we compare the spatial and temporal patterns of Plasmodium falciparum EIR and PR using data collected over 38 months in a rural area of Malawi. We then quantify the relationship between EIR and PR by using empirical and mechanistic statistical models.

Results

Hotspots identified through the EIR and PR partly overlapped during high transmission seasons but not during low transmission seasons. The estimated relationship showed a 1-month delayed effect of EIR on PR such that at lower levels of EIR, increases in EIR are associated with rapid rise in PR, whereas at higher levels of EIR, changes in EIR do not translate into notable changes in PR.

Conclusions

Our study emphasises the need for integrated malaria control strategies that combine vector and human host managements monitored by both entomological and parasitaemia indices.

Funding

This work was supported by Stichting Dioraphte grant number 13050800.

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.

Estimating malaria chemoprevention and vector control coverage using program and campaign data: A scoping review of current practices and opportunities

Background

Accurate estimation of intervention coverage is a vital component of malaria program monitoring and evaluation, both for process evaluation (how well program targets are achieved), and impact evaluation (whether intervention coverage had an impact on malaria burden). There is growing interest in maximizing the utility of program data to generate interim estimates of intervention coverage in the periods between large-scale cross-sectional surveys (the gold standard). As such, this study aimed to identify relevant concepts and themes that may guide future optimization of intervention coverage estimation using routinely collected data, or data collected during and following intervention campaigns, with a particular focus on strategies to define the denominator.

Methods

We conducted a scoping review of current practices to estimate malaria intervention coverage for insecticide-treated nets (ITNs); indoor residual spray (IRS); intermittent preventive treatment in pregnancy (IPTp); mass drug administration (MDA); and seasonal malaria chemoprevention (SMC) interventions; case management was excluded. Multiple databases were searched for relevant articles published from January 1, 2015 to June 1, 2018. Additionally, we identified and included other guidance relevant to estimating population denominators, with a focus on innovative techniques.

Results

While program data have the potential to provide intervention coverage data, there are still substantial challenges in selecting appropriate denominators. The review identified a lack of consistency in how coverage was defined and reported for each intervention type, with denominator estimation methods not clearly or consistently reported, and denominator estimates rarely triangulated with other data sources to present the feasible range of denominator values and consequently the range of likely coverage estimates.

Conclusions

Though household survey-based estimates of intervention coverage remain the gold standard, efforts should be made to further standardize practices for generating interim measurements of intervention coverage from program data, and for estimating and reporting population denominators. This includes fully describing any projections or adjustments made to existing census or population data, exploring opportunities to validate available data by comparing with other sources, and explaining how the denominator has been restricted (or not) to reflect exclusion criteria.

Effectiveness of spatially targeted interventions for control of HIV, tuberculosis, leprosy and malaria: a systematic review

BACKGROUND

As infectious diseases approach global elimination targets, spatial targeting is increasingly important to identify community hotspots of transmission and effectively target interventions. We aimed to synthesise relevant evidence to define best practice approaches and identify policy and research gaps.

OBJECTIVE

To systematically appraise evidence for the effectiveness of spatially targeted community public health interventions for HIV, tuberculosis (TB), leprosy and malaria.

DESIGN

Systematic review.

DATA SOURCES

We searched Medline, Embase, Global Health, Web of Science and Cochrane Database of Systematic Reviews between 1 January 1993 and 22 March 2021.

STUDY SELECTION

The studies had to include HIV or TB or leprosy or malaria and spatial hotspot definition, and community interventions.

DATA EXTRACTION AND SYNTHESIS

A data extraction tool was used. For each study, we summarised approaches to identifying hotpots, intervention design and effectiveness of the intervention.

RESULTS

Ten studies, including one cluster randomised trial and nine with alternative designs (before-after, comparator area), satisfied our inclusion criteria. Spatially targeted interventions for HIV (one USA study), TB (three USA) and leprosy (two Brazil, one Federated States of Micronesia) each used household location and disease density to define hotspots followed by community-based screening. Malaria studies (one each from India, Indonesia and Kenya) used household location and disease density for hotspot identification followed by complex interventions typically combining community screening, larviciding of stagnant water bodies, indoor residual spraying and mass drug administration. Evidence of effect was mixed.

CONCLUSIONS

Studies investigating spatially targeted interventions were few in number, and mostly underpowered or otherwise limited methodologically, affecting interpretation of intervention impact. Applying advanced epidemiological methodologies supporting more robust hotspot identification and larger or more intensive interventions would strengthen the evidence-base for this increasingly important approach.

PROSPERO REGISTRATION NUMBER

CRD42019130133.

The application of drones for mosquito larval habitat identification in rural environments: a practical approach for malaria control?

BACKGROUND

Spatio-temporal trends in mosquito-borne diseases are driven by the locations and seasonality of larval habitat. One method of disease control is to decrease the mosquito population by modifying larval habitat, known as larval source management (LSM). In malaria control, LSM is currently considered impractical in rural areas due to perceived difficulties in identifying target areas. High resolution drone mapping is being considered as a practical solution to address this barrier. In this paper, the authors' experiences of drone-led larval habitat identification in Malawi were used to assess the feasibility of this approach.

METHODS

Drone mapping and larval surveys were conducted in Kasungu district, Malawi between 2018 and 2020. Water bodies and aquatic vegetation were identified in the imagery using manual methods and geographical object-based image analysis (GeoOBIA) and the performances of the classifications were compared. Further, observations were documented on the practical aspects of capturing drone imagery for informing malaria control including cost, time, computing, and skills requirements. Larval sampling sites were characterized by biotic factors visible in drone imagery and generalized linear mixed models were used to determine their association with larval presence.

RESULTS

Imagery covering an area of 8.9 km² across eight sites was captured. Larval habitat characteristics were successfully identified using GeoOBIA on images captured by a standard camera (median accuracy = 98%) with no notable improvement observed after incorporating data from a near-infrared sensor. This approach however required greater processing time and technical skills compared to manual identification. Larval samples captured from 326 sites confirmed that drone-captured characteristics, including aquatic vegetation presence and type, were significantly associated with larval presence.

CONCLUSIONS

This study demonstrates the potential for drone-acquired imagery to support mosquito larval habitat identification in rural, malaria-endemic areas, although technical challenges were identified which may hinder the scale up of this approach. Potential solutions have however been identified, including strengthening linkages with the flourishing drone industry in countries such as Malawi. Further consultations are therefore needed between experts in the fields of drones, image analysis and vector control are needed to develop more detailed guidance on how this technology can be most effectively exploited in malaria control.

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.

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

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

Effectiveness and cost-effectiveness of reactive, targeted indoor residual spraying for malaria control in low-transmission settings: a cluster-randomised, non-inferiority trial in South Africa

BACKGROUND

Increasing insecticide costs and constrained malaria budgets could make universal vector control strategies, such as indoor residual spraying (IRS), unsustainable in low-transmission settings. We investigated the effectiveness and cost-effectiveness of a reactive, targeted IRS strategy.

METHODS

This cluster-randomised, open-label, non-inferiority trial compared reactive, targeted IRS with standard IRS practice in northeastern South Africa over two malaria seasons (2015-17). In standard IRS clusters, programme managers conducted annual mass spray campaigns prioritising areas using historical data, expert opinion, and other factors. In targeted IRS clusters, only houses of index cases (identified through passive surveillance) and their immediate neighbours were sprayed. The non-inferiority margin was 1 case per 1000 person-years. Health service costs of real-world implementation were modelled from primary and secondary data. Incremental costs per disability-adjusted life-year (DALY) were estimated and deterministic and probabilistic sensitivity analyses conducted. This study is registered with ClinicalTrials.gov, NCT02556242.

FINDINGS

Malaria incidence was 0·95 per 1000 person-years (95% CI 0·58 to 1·32) in the standard IRS group and 1·05 per 1000 person-years (0·72 to 1·38) in the targeted IRS group, corresponding to a rate difference of 0·10 per 1000 person-years (-0·38 to 0·59), demonstrating non-inferiority for targeted IRS (p<0·0001). Per additional DALY incurred, targeted IRS saved US$7845 (2902 to 64 907), giving a 94-98% probability that switching to targeted IRS would be cost-effective relative to plausible cost-effectiveness thresholds for South Africa ($2637 to $3557 per DALY averted). Depending on the threshold used, targeted IRS would remain cost-effective at incidences of less than 2·0-2·7 per 1000 person-years. Findings were robust to plausible variation in other parameters.

INTERPRETATION

Targeted IRS was non-inferior, safe, less costly, and cost-effective compared with standard IRS in this very-low-transmission setting. Saved resources could be reallocated to other malaria control and elimination activities.

FUNDING

Joint Global Health Trials.

Multi-Indicator and Multistep Assessment of Malaria Transmission Risks in Western Kenya

Malaria risk factor assessment is a critical step in determining cost-effective intervention strategies and operational plans in a regional setting. We develop a multi-indicator multistep approach to model the malaria risks at the population level in western Kenya. We used a combination of cross-sectional seasonal malaria infection prevalence, vector density, and cohort surveillance of malaria incidence at the village level to classify villages into malaria risk groups through unsupervised classification. Generalized boosted multinomial logistics regression analysis was performed to determine village-level risk factors using environmental, biological, socioeconomic, and climatic features. Thirty-six villages in western Kenya were first classified into two to five operational groups based on different combinations of malaria risk indicators. Risk assessment indicated that altitude accounted for 45-65% of all importance value relative to all other factors; all other variable importance values were < 6% in all models. After adjusting by altitude, villages were classified into three groups within distinct geographic areas regardless of the combination of risk indicators. Risk analysis based on altitude-adjusted classification indicated that factors related to larval habitat abundance accounted for 63% of all importance value, followed by geographic features related to the ponding effect (17%), vegetation cover or greenness (15%), and the number of bed nets combined with February temperature (5%). These results suggest that altitude is the intrinsic factor in determining malaria transmission risk in western Kenya. Malaria vector larval habitat management, such as habitat reduction and larviciding, may be an important supplement to the current first-line vector control tools in the study area.

Malaria in Southern Venezuela: The hottest hotspot in Latin America

Malaria elimination in Latin America is becoming an elusive goal. Malaria cases reached a historical ~1 million in 2017 and 2018, with Venezuela contributing 53% and 51% of those cases, respectively. Historically, malaria incidence in southern Venezuela has accounted for most of the country's total number of cases. The efficient deployment of disease prevention measures and prediction of disease spread to new regions requires an in-depth understanding of spatial heterogeneity on malaria transmission dynamics. Herein, we characterized the spatial epidemiology of malaria in southern Venezuela from 2007 through 2017 and described the extent to which malaria distribution has changed country-wide over the recent years. We found that disease transmission was focal and more prevalent in the southeast region of southern Venezuela where two persistent hotspots of Plasmodium vivax (76%) and P. falciparum (18%) accounted for ~60% of the total number of cases. Such hotspots are linked to deforestation as a consequence of illegal gold mining activities. Incidence has increased nearly tenfold over the last decade, showing an explosive epidemic growth due to a significant lack of disease control programs. Our findings highlight the importance of spatially oriented interventions to contain the ongoing malaria epidemic in Venezuela. This work also provides baseline epidemiological data to assess cross-border malaria dynamics and advocates for innovative control efforts in the Latin American region.

Near-term climate change impacts on sub-national malaria transmission

The role of climate change on global malaria is often highlighted in World Health Organisation reports. We modelled a Zambian socio-environmental dataset from 2000 to 2016, against malaria trends and investigated the relationship of near-term environmental change with malaria incidence using Bayesian spatio-temporal, and negative binomial mixed regression models. We introduced the diurnal temperature range (DTR) as an alternative environmental measure to the widely used mean temperature. We found substantial sub-national near-term variations and significant associations with malaria incidence-trends. Significant spatio-temporal shifts in DTR/environmental predictors influenced malaria incidence-rates, even in areas with declining trends. We highlight the impact of seasonally sensitive DTR, especially in the first two quarters of the year and demonstrate how substantial investment in intervention programmes is negatively impacted by near-term climate change, most notably since 2010. We argue for targeted seasonally-sensitive malaria chemoprevention programmes.

Targeting Malaria Hotspots to Reduce Transmission Incidence in Senegal

In central Senegal, malaria incidence declined in response to scaling-up of control measures from 2000 to 2010 and has since remained stable, making elimination unlikely in the short term. Additional control measures are needed to reduce transmission. We simulated chemoprophylaxis interventions targeting malaria hotspots using a metapopulation mathematical model, based on a differential-equation framework and incorporating human mobility. The model was fitted to weekly malaria incidence from 45 villages. Three approaches for selecting intervention targets were compared: (a) villages with malaria cases during the low transmission season of the previous year; (b) villages with highest incidence during the high transmission season of the previous year; (c) villages with highest connectivity with adjacent populations. Our results showed that intervention strategies targeting hotspots would be effective in reducing malaria incidence in both targeted and untargeted areas. Regardless of the intervention strategy used, pre-elimination (1-5 cases per 1000 per year) would not be reached without simultaneously increasing vector control by more than 10%. A cornerstone of malaria control and elimination is the effective targeting of strategic locations. Mathematical tools help to identify those locations and estimate the impact in silico.

The Impact of Three Years of Targeted Indoor Residual Spraying with Pirimiphos-Methyl on Household Vector Abundance in a High Malaria Transmission Area of Northern Zambia

The global malaria burden has decreased substantially, but gains have been uneven both within and between countries. In Zambia, the malaria burden remains high in northern and eastern regions of the country. To effectively reduce malaria transmission in these areas, evidence-based intervention strategies are needed. Zambia’s National Malaria Control Centre conducted targeted indoor residual spraying (IRS) in 40 high-burden districts from 2014 to 2016 using the novel organophosphate insecticide pirimiphos-methyl. The Southern and Central Africa International Centers of Excellence for Malaria Research conducted an evaluation of the impact of the IRS campaign on household vector abundance in Nchelenge District, Luapula Province. From April 2012 to July 2017, field teams conducted indoor overnight vector collections from 25 to 30 households per month using Centers for Disease Control light traps. Changes in indoor anopheline counts before versus after IRS were assessed by species using negative binomial regression models with robust standard errors, controlling for geographic and climatological covariates. Counts of Anopheles funestus declined by approximately 50% in the study area and within areas targeted for IRS, and counts of Anopheles gambiae declined by approximately 40%. Within targeted areas, An. funestus counts declined more in sprayed households than in unsprayed households; however, this relationship was not observed for An. gambiae. The moderate decrease in indoor vector abundance indicates that IRS with pirimiphos-methyl is an effective vector control measure, but a more comprehensive package of interventions is needed with sufficient coverage to effectively reduce the malaria burden in this setting.

Spatial-temporal patterns of malaria incidence in Uganda using HMIS data from 2015 to 2019

BACKGROUND

As global progress to reduce malaria transmission continues, it is increasingly important to track changes in malaria incidence rather than prevalence. Risk estimates for Africa have largely underutilized available health management information systems (HMIS) data to monitor trends. This study uses national HMIS data, together with environmental and geographical data, to assess spatial-temporal patterns of malaria incidence at facility catchment level in Uganda, over a recent 5-year period.

METHODS

Data reported by 3446 health facilities in Uganda, between July 2015 and September 2019, was analysed. To assess the geographic accessibility of the health facilities network, AccessMod was employed to determine a three-hour cost-distance catchment around each facility. Using confirmed malaria cases and total catchment population by facility, an ecological Bayesian conditional autoregressive spatial-temporal Poisson model was fitted to generate monthly posterior incidence rate estimates, adjusted for caregiver education, rainfall, land surface temperature, night-time light (an indicator of urbanicity), and vegetation index.

RESULTS

An estimated 38.8 million (95% Credible Interval [CI]: 37.9-40.9) confirmed cases of malaria occurred over the period, with a national mean monthly incidence rate of 20.4 (95% CI: 19.9-21.5) cases per 1000, ranging from 8.9 (95% CI: 8.7-9.4) to 36.6 (95% CI: 35.7-38.5) across the study period. Strong seasonality was observed, with June-July experiencing highest peaks and February-March the lowest peaks. There was also considerable geographic heterogeneity in incidence, with health facility catchment relative risk during peak transmission months ranging from 0 to 50.5 (95% CI: 49.0-50.8) times higher than national average. Both districts and health facility catchments showed significant positive spatial autocorrelation; health facility catchments had global Moran's I = 0.3 (p < 0.001) and districts Moran's I = 0.4 (p < 0.001). Notably, significant clusters of high-risk health facility catchments were concentrated in Acholi, West Nile, Karamoja, and East Central - Busoga regions.

CONCLUSION

Findings showed clear countrywide spatial-temporal patterns with clustering of malaria risk across districts and health facility catchments within high risk regions, which can facilitate targeting of interventions to those areas at highest risk. Moreover, despite high and perennial transmission, seasonality for malaria incidence highlights the potential for optimal and timely implementation of targeted interventions.

Malaria hotspots explained from the perspective of ecological theory underlying insect foraging

Hotspots constitute the major reservoir for residual malaria transmission, with higher malaria incidence than neighbouring areas, and therefore, have the potential to form the cornerstone for successful intervention strategies. Detection of malaria hotspots is hampered by their heterogenous spatial distribution, and the laborious nature and low sensitivity of the current methods used to assess transmission intensity. We adopt ecological theory underlying foraging in herbivorous insects to vector mosquito host seeking and modelling of fine-scale landscape features at the village level. The overall effect of environmental variables on the density of indoor mosquitoes, sporozoite infected mosquitoes, and malaria incidence, was determined using generalized linear models. Spatial analyses were used to identify hotspots for malaria incidence, as well as malaria vector density and associated sporozoite prevalence. We identify household occupancy and location as the main predictors of vector density, entomological inoculation rate and malaria incidence. We propose that the use of conventional vector control and malaria interventions, integrated with their intensified application targeting predicted hotspots, can be used to reduce malaria incidence in endemic and residual malaria settings.

How useful are malaria risk maps at the country level? Perceptions of decision-makers in Kenya, Malawi and the Democratic Republic of Congo

Background

Declining malaria prevalence and pressure on external funding have increased the need for efficiency in malaria control in sub-Saharan Africa (SSA). Modelled Plasmodium falciparum parasite rate (PfPR) maps are increasingly becoming available and provide information on the epidemiological situation of countries. However, how these maps are understood or used for national malaria planning is rarely explored. In this study, the practices and perceptions of national decision-makers on the utility of malaria risk maps, showing prevalence of parasitaemia or incidence of illness, was investigated.

Methods

A document review of recent National Malaria Strategic Plans was combined with 64 in-depth interviews with stakeholders in Kenya, Malawi and the Democratic Republic of Congo (DRC). The document review focused on the type of epidemiological maps included and their use in prioritising and targeting interventions. Interviews (14 Kenya, 17 Malawi, 27 DRC, 6 global level) explored drivers of stakeholder perceptions of the utility, value and limitations of malaria risk maps.

Results

Three different types of maps were used to show malaria epidemiological strata: malaria prevalence using a PfPR modelled map (Kenya); malaria incidence using routine health system data (Malawi); and malaria prevalence using data from the most recent Demographic and Health Survey (DRC). In Kenya the map was used to target preventative interventions, including long-lasting insecticide-treated nets (LLINs) and intermittent preventive treatment in pregnancy (IPTp), whilst in Malawi and DRC the maps were used to target in-door residual spraying (IRS) and LLINs distributions in schools. Maps were also used for operational planning, supply quantification, financial justification and advocacy. Findings from the interviews suggested that decision-makers lacked trust in the modelled PfPR maps when based on only a few empirical data points (Malawi and DRC).

Conclusions

Maps were generally used to identify areas with high prevalence in order to implement specific interventions. Despite the availability of national level modelled PfPR maps in all three countries, they were only used in one country. Perceived utility of malaria risk maps was associated with the epidemiological structure of the country and use was driven by perceived need, understanding (quality and relevance), ownership and trust in the data used to develop the maps.

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

BACKGROUND

Passively collected malaria case data are the foundation for public health decision making. However, because of population-level immunity, infections might not always be sufficiently symptomatic to prompt individuals to seek care. Understanding the proportion of all Plasmodium spp infections expected to be detected by the health system becomes particularly paramount in elimination settings. The aim of this study was to determine the association between the proportion of infections detected and transmission intensity for Plasmodium falciparum and Plasmodium vivax in several global endemic settings.

METHODS

The proportion of infections detected in routine malaria data, P(Detect), was derived from paired household cross-sectional survey and routinely collected malaria data within health facilities. P(Detect) was estimated using a Bayesian model in 431 clusters spanning the Americas, Africa, and Asia. The association between P(Detect) and malaria prevalence was assessed using log-linear regression models. Changes in P(Detect) over time were evaluated using data from 13 timepoints over 2 years from The Gambia.

FINDINGS

The median estimated P(Detect) across all clusters was 12·5% (IQR 5·3-25·0) for P falciparum and 10·1% (5·0-18·3) for P vivax and decreased as the estimated log-PCR community prevalence increased (adjusted odds ratio [OR] for P falciparum 0·63, 95% CI 0·57-0·69; adjusted OR for P vivax 0·52, 0·47-0·57). Factors associated with increasing P(Detect) included smaller catchment population size, high transmission season, improved care-seeking behaviour by infected individuals, and recent increases (within the previous year) in transmission intensity.

INTERPRETATION

The proportion of all infections detected within health systems increases once transmission intensity is sufficiently low. The likely explanation for P falciparum is that reduced exposure to infection leads to lower levels of protective immunity in the population, increasing the likelihood that infected individuals will become symptomatic and seek care. These factors might also be true for P vivax but a better understanding of the transmission biology is needed to attribute likely reasons for the observed trend. In low transmission and pre-elimination settings, enhancing access to care and improvements in care-seeking behaviour of infected individuals will lead to an increased proportion of infections detected in the community and might contribute to accelerating the interruption of transmission.

FUNDING

Wellcome Trust.

Leveraging risk maps of malaria vector abundance to guide control efforts reduces malaria incidence in Eastern Province, Zambia

Although transmission of malaria and other mosquito-borne diseases is geographically heterogeneous, in sub-Saharan Africa risk maps are rarely used to determine which communities receive vector control interventions. We compared outcomes in areas receiving different indoor residual spray (IRS) strategies in Eastern Province, Zambia: (1) concentrating IRS interventions within a geographical area, (2) prioritizing communities to receive IRS based on predicted probabilities of Anopheles funestus, and (3) prioritizing communities to receive IRS based on observed malaria incidence at nearby health centers. Here we show that the use of predicted probabilities of An. funestus to guide IRS implementation saw the largest decrease in malaria incidence at health centers, a 13% reduction (95% confidence interval = 5-21%) compared to concentrating IRS geographically and a 37% reduction (95% confidence interval = 30-44%) compared to targeting IRS based on health facility incidence. These results suggest that vector control programs could produce better outcomes by prioritizing IRS according to malaria-vector risk maps.

How to Estimate Optimal Malaria Readiness Indicators at Health-District Level: Findings from the Burkina Faso Service Availability and Readiness Assessment (SARA) Data

One of the major contributors of malaria-related deaths in Sub-Saharan African countries is the limited accessibility to quality care. In these countries, malaria control activities are implemented at the health-district level (operational entity of the national health system), while malaria readiness indicators are regionally representative. This study provides an approach for estimating health district-level malaria readiness indicators from survey data designed to provide regionally representative estimates. A binomial-hierarchical Bayesian spatial prediction method was applied to Burkina Faso Service Availability and Readiness Assessment (SARA) survey data to provide estimates of essential equipment availability and readiness for malaria care. Predicted values of each indicator were adjusted by the type of health facility, location, and population density. Then, a health district composite readiness profile was built via hierarchical ascendant classification. All surveyed health-facilities were mandated by the Ministry of Health to manage malaria cases. The spatial distribution of essential equipment and malaria readiness was heterogeneous. Around 62.9% of health districts had a high level of readiness to provide malaria care and prevention during pregnancy. Low-performance scores for managing malaria cases were found in big cities. Health districts with low coverage for both first-line antimalarial drugs and rapid diagnostic tests were Baskuy, Bogodogo, Boulmiougou, Nongr-Massoum, Sig-Nonghin, Dafra, and Do. We provide health district estimates and reveal gaps in basic equipment and malaria management resources in some districts that need to be filled. By providing local-scale estimates, this approach could be replicated for other types of indicators to inform decision makers and health program managers and to identify priority areas.

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.

Effectiveness of reactive focal mass drug administration and reactive focal vector control to reduce malaria transmission in the low malaria-endemic setting of Namibia: a cluster-randomised controlled, open-label, two-by-two factorial design trial

BACKGROUND

In low malaria-endemic settings, screening and treatment of individuals in close proximity to index cases, also known as reactive case detection (RACD), is practised for surveillance and response. However, other approaches could be more effective for reducing transmission. We aimed to evaluate the effectiveness of reactive focal mass drug administration (rfMDA) and reactive focal vector control (RAVC) in the low malaria-endemic setting of Zambezi (Namibia).

METHODS

We did a cluster-randomised controlled, open-label trial using a two-by-two factorial design of 56 enumeration area clusters in the low malaria-endemic setting of Zambezi (Namibia). We randomly assigned these clusters using restricted randomisation to four groups: RACD only, rfMDA only, RAVC plus RACD, or rfMDA plus RAVC. RACD involved rapid diagnostic testing and treatment with artemether-lumefantrine and single-dose primaquine, rfMDA involved presumptive treatment with artemether-lumefantrine, and RAVC involved indoor residual spraying with pirimiphos-methyl. Interventions were administered within 500 m of index cases. To evaluate the effectiveness of interventions targeting the parasite reservoir in humans (rfMDA vs RACD), in mosquitoes (RAVC vs no RAVC), and in both humans and mosquitoes (rfMDA plus RAVC vs RACD only), an intention-to-treat analysis was done. For each of the three comparisons, the primary outcome was the cumulative incidence of locally acquired malaria cases. This trial is registered with ClinicalTrials.gov, number NCT02610400.

FINDINGS

Between Jan 1, 2017, and Dec 31, 2017, 55 enumeration area clusters had 1118 eligible index cases that led to 342 interventions covering 8948 individuals. The cumulative incidence of locally acquired malaria was 30·8 per 1000 person-years (95% CI 12·8-48·7) in the clusters that received rfMDA versus 38·3 per 1000 person-years (23·0-53·6) in the clusters that received RACD; 30·2 per 1000 person-years (15·0-45·5) in the clusters that received RAVC versus 38·9 per 1000 person-years (20·7-57·1) in the clusters that did not receive RAVC; and 25·0 per 1000 person-years (5·2-44·7) in the clusters that received rfMDA plus RAVC versus 41·4 per 1000 person-years (21·5-61·2) in the clusters that received RACD only. After adjusting for imbalances in baseline and implementation factors, the incidence of malaria was lower in clusters receiving rfMDA than in those receiving RACD (adjusted incidence rate ratio 0·52 [95% CI 0·16-0·88], p=0·009), lower in clusters receiving RAVC than in those that did not (0·48 [0·16-0·80], p=0·002), and lower in clusters that received rfMDA plus RAVC than in those receiving RACD only (0·26 [0·10-0·68], p=0·006). No serious adverse events were reported.

INTERPRETATION

In a low malaria-endemic setting, rfMDA and RAVC, implemented alone and in combination, reduced malaria transmission and should be considered as alternatives to RACD for elimination of malaria.

FUNDING

Novartis Foundation, Bill & Melinda Gates Foundation, and Horchow Family Fund.

Risk factors for Plasmodium falciparum infection in the Kenyan Highlands: a cohort study

BACKGROUND

Malaria transmission in African highland areas can be prone to epidemics, with minor fluctuations in temperature or altitude resulting in highly heterogeneous transmission. In the Kenyan Highlands, where malaria prevalence has been increasing, characterising malaria incidence and identifying risk factors for infection is complicated by asymptomatic infection.

METHODS

This all-age cohort study, one element of the Malaria Transmission Consortium, involved monthly follow-up of 3155 residents of the Kisii and Rachuonyo South districts during June 2009-June 2010. Participants were tested for malaria using rapid diagnostic testing at every visit, regardless of symptoms.

RESULTS

The incidence of Plasmodium falciparum infection was 0.2 cases per person, although infections were clustered within individuals and over time, with the majority of infections detected in the last month of the cohort study. Overall, incidence was higher in the Rachuonyo district and infections were detected most frequently in 5-10-year-olds. The majority of infections were asymptomatic (58%). Travel away from the study area was a notable risk factor for infection.

CONCLUSIONS

Identifying risk factors for malaria infection can help to guide targeting of interventions to populations most likely to be exposed to malaria.

The Impact of 3 Years of Targeted Indoor Residual Spraying With Pirimiphos-Methyl on Malaria Parasite Prevalence in a High-Transmission Area of Northern Zambia

Malaria transmission in northern Zambia has increased in the past decade, despite malaria control activities. Evidence-based intervention strategies are needed to effectively reduce malaria transmission. Zambia's National Malaria Control Centre conducted targeted indoor residual spraying (IRS) in Nchelenge District, Luapula Province, from 2014 to 2016 using the organophosphate insecticide pirimiphos-methyl. An evaluation of the IRS campaign was conducted by the Southern Africa International Centers of Excellence for Malaria Research using actively detected malaria cases in bimonthly household surveys carried out from April 2012 to July 2017. Changes in malaria parasite prevalence after IRS were assessed by season using Poisson regression models with robust standard errors, controlling for clustering of participants in households and demographic, geographical, and climatological covariates. In targeted areas, parasite prevalence declined approximately 25% during the rainy season following IRS with pirimiphos-methyl but did not decline during the dry season or in the overall study area. Within targeted areas, parasite prevalence declined in unsprayed households, suggesting both direct and indirect effects of IRS. The moderate decrease in parasite prevalence within sprayed areas indicates that IRS with pirimiphos-methyl is an effective malaria control measure, but a more comprehensive package of interventions is needed to effectively reduce the malaria burden in this setting.

Malaria hot spot along the foothills of Rakhine state, Myanmar: geospatial distribution of malaria cases in townships targeted for malaria elimination

Background

Myanmar has targeted elimination of malaria by 2030. In three targeted townships of Rakhine state of Myanmar, a project is being piloted to eliminate malaria by 2025. The comprehensive case investigation (CCI) and geotagging of cases by health workers is a core activity under the project. However, the CCI data is not analyzed for obtaining information on geospatial distribution of cases and timeliness of diagnosis. In this regard, we aimed to depict geospatial distribution and assess the proportion with delayed diagnosis among diagnosed malaria cases residing in three targeted townships during April 2018 to March 2019.

Methods

This was a cross sectional analysis of CCI data routinely collected by national malaria control programme. The geocode (latitude and longitude) of the address was analysed using Quantum Geographic Information System software to deduce spot maps and hotspots of cases. The EpiData analysis software was used to summarize the proportion with delay in diagnosis (diagnosed ≥24 hours after the fever onset).

Results

Of the 171 malaria cases diagnosed during study period, the CCI was conducted in 157 (92%) cases. Of them, 127 (81%) cases reported delay in diagnosis, 138 (88%) cases were indigenous who got infection within the township and 13 (8%) were imported from outside the township. Malaria hotspots were found along the foothills with increase in cases during the rainy season. The indigenous cases were concentrated over the foothills in the northern and southern borders of Toungup township.

Conclusion

In the targeted townships for malaria elimination, the high proportion of the cases was indigenous and clustered at the foothill areas during rainy season. The programme should strengthen case surveillance and healthcare services in the areas with aggregation of cases to eliminate the malaria in the township. As high majority of patients have delayed diagnosis, the reasons for delay has to be explored and corrective measures needs to be taken.

Spatial distribution of Anopheles gambiae sensu lato larvae in the urban environment of Yaoundé, Cameroon

Background

The rapid and unplanned urbanization of African cities is considered to increase the risk of urban malaria transmission. The present study objective was to assess factors influencing the spatio-temporal distribution of Anopheles gambiae s.l. larvae in the city of Yaoundé, Cameroon.

Methods

All water bodies were checked once every 2 months for the presence of mosquito larvae from March 2017 to May 2018 in 32 districts of Yaoundé. Physico-chemical characteristics including the size, depth, turbidity, pH, temperature, conductivity, sulfates, organophosphates, hydrogen peroxide (H₂O₂), conductivity, iron and calcium were recorded and analyzed according to anopheline larvae presence or absence. High resolution satellite images from landsat sentinel Enhanced Thematic Mapper were used for spatial mapping of both field and environmental variables. Bivariate and multivariate logistic regression models were used to identify variables closely associated with anopheline larvae distribution.

Results

A total of 18 696 aquatic habitats were checked and only 2942 sites (15.7%) contained anopheline larvae. A high number of sites with anopheline larvae (≥ 69%) presented late instar larvae (L3, L4 and pupae). Anopheline mosquito larvae were sampled from a variety of breeding sites including puddles (51.6%), tire prints (12.9%), wells (11.7%) and drains (11.3%). Bivariate logistic regression analyses associated anopheline larvae presence with the absence of predators, absence of algae, absence of vegetation and depth of less than 1 m. Conductivity, turbidity, organophosphates, H₂O₂ and temperature were significantly high in breeding sites with anopheline larvae than in breeding sites without these larvae (P <  0.1). Anopheline species collected included An. coluzzii (91.1%) and An. gambiae s.s. (8.9%). GIS mapping indicated a heterogeneous distribution of anopheline breeding habitats in the city of Yaoundé. Land cover analysis indicated high variability of the city of Yaoundé’s landscape.

Conclusions

The data confirms adaptation of An. gambiae s.l. to the urban domain in the city of Yaoundé and calls for urgent actions to improve malaria vector control.

Malaria Hotspots: Is There Epidemiological Evidence for Fine-Scale Spatial Targeting of Interventions?

As data at progressively granular spatial scales become available, the temptation is to target interventions to areas with higher malaria transmission - so-called hotspots - with the aim of reducing transmission in the wider community. This paper reviews literature to determine if hotspots are an intrinsic feature of malaria epidemiology and whether current evidence supports hotspot-targeted interventions. Hotspots are a consistent feature of malaria transmission at all endemicities. The smallest spatial unit capable of supporting transmission is the household, where peri-domestic transmission occurs. Whilst the value of focusing interventions to high-burden areas is evident, there is currently limited evidence that local-scale hotspots fuel transmission. As boundaries are often uncertain, there is no conclusive evidence that hotspot-targeted interventions accelerate malaria elimination.

"Spatial heterogeneity of environmental risk in randomized prevention trials: consequences and modeling"

Background

In the context of environmentally influenced communicable diseases, proximity to environmental sources results in spatial heterogeneity of risk, which is sometimes difficult to measure in the field. Most prevention trials use randomization to achieve comparability between groups, thus failing to account for heterogeneity.

This study aimed to determine under what conditions spatial heterogeneity biases the results of randomized prevention trials, and to compare different approaches to modeling this heterogeneity.

Methods

Using the example of a malaria prevention trial, simulations were performed to quantify the impact of spatial heterogeneity and to compare different models.

Simulated scenarios combined variation in baseline risk, a continuous protective factor (age), a non-related factor (sex), and a binary protective factor (preventive treatment). Simulated spatial heterogeneity scenarios combined variation in breeding site density and effect, location, and population density.

The performances of the following five statistical models were assessed: a non-spatial Cox Proportional Hazard (Cox-PH) model and four models accounting for spatial heterogeneity—i.e., a Data-Generating Model, a Generalized Additive Model (GAM), and two Stochastic Partial Differential Equation (SPDE) models, one modeling survival time and the other the number of events. Using a Bayesian approach, we estimated the SPDE models with an Integrated Nested Laplace Approximation algorithm.

For each factor (age, sex, treatment), model performances were assessed by quantifying parameter estimation biases, mean square errors, confidence interval coverage rates (CRs), and significance rates. The four models were applied to data from a malaria transmission blocking vaccine candidate.

Results

The level of baseline risk did not affect our estimates. However, with a high breeding site density and a strong breeding site effect, the Cox-PH and GAM models underestimated the age and treatment effects (but not the sex effect) with a low CR.

When population density was low, the Cox-SPDE model slightly overestimated the effect of related factors (age, treatment). The two SPDE models corrected the impact of spatial heterogeneity, thus providing the best estimates.

Conclusion

Our results show that when spatial heterogeneity is important but not measured, randomization alone cannot achieve comparability between groups. In such cases, prevention trials should model spatial heterogeneity with an adapted method.

Trial registration

The dataset used for the application example was extracted from Vaccine Trial #NCT02334462 (ClinicalTrials.gov registry).

Electronic supplementary material

The online version of this article (10.1186/s12874-019-0759-z) contains supplementary material, which is available to authorized users.

Outbreak analytics: a developing data science for informing the response to emerging pathogens

Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics, an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Distinct Antibody Signatures Associated with Different Malaria Transmission Intensities in Zambia and Zimbabwe

Antibodies to Plasmodium falciparum are specific biomarkers that can be used to monitor parasite exposure over broader time frames than microscopy, rapid diagnostic tests, or molecular assays. Consequently, seroprevalence surveys can assist with monitoring the impact of malaria control interventions, particularly in the final stages of elimination, when parasite incidence is low. The protein array format to measure antibodies to diverse P. falciparum antigens requires only small sample volumes and is high throughput, permitting the monitoring of malaria transmission on large spatial and temporal scales. We expanded the use of a protein microarray to assess malaria transmission in settings beyond those with a low malaria incidence. Antibody responses in children and adults were profiled, using a P. falciparum protein microarray, through community-based surveys in three areas in Zambia and Zimbabwe at different stages of malaria control and elimination. These three epidemiological settings had distinct serological profiles reflective of their malaria transmission histories. While there was little correlation between transmission intensity and antibody signals (magnitude or breadth) in adults, there was a clear correlation in children younger than 5 years of age. Antibodies in adults appeared to be durable even in the absence of significant recent transmission, whereas antibodies in children provided a more accurate picture of recent levels of transmission intensity. Seroprevalence studies in children could provide a valuable marker of progress toward malaria elimination.IMPORTANCE As malaria approaches elimination in many areas of the world, monitoring the effect of control measures becomes more important but challenging. Low-level infections may go undetected by conventional tests that depend on parasitemia, particularly in immune individuals, who typically show no symptoms of malaria. In contrast, antibodies persist after parasitemia and may provide a more accurate picture of recent exposure. Only a few parasite antigens-mainly vaccine candidates-have been evaluated in seroepidemiological studies. We examined antibody responses to 500 different malaria proteins in blood samples collected through community-based surveillance from areas with low, medium, and high malaria transmission intensities. The breadth of the antibody responses in adults was broad in all three settings and was a poor correlate of recent exposure. In contrast, children represented a better sentinel population for monitoring recent malaria transmission. These data will help inform the use of multiplex serology for malaria surveillance.

Spatially targeted screening to reduce tuberculosis transmission in high-incidence settings

As the leading infectious cause of death worldwide and the primary proximal cause of death in individuals living with HIV, tuberculosis remains a global concern. Existing tuberculosis control strategies that rely on passive case-finding appear insufficient to achieve targets for reductions in tuberculosis incidence and mortality. Active case-finding strategies aim to detect infectious individuals earlier in their infectious period to reduce onward transmission and improve treatment outcomes. Empirical studies of active case-finding have produced mixed results and determining how to direct active screening to those most at risk remains a topic of intense research. Our systematic review of literature evaluating the effects of geographically targeted tuberculosis screening interventions found three studies in low tuberculosis incidence settings, but none conducted in high tuberculosis incidence countries. We discuss open questions related to the use of spatially targeted approaches for active screening in countries where tuberculosis incidence is highest.

Socioeconomic and environmental factors associated with malaria hotspots in the Nanoro demographic surveillance area, Burkina Faso

BACKGROUND

With limited resources and spatio-temporal heterogeneity of malaria in developing countries, it is still difficult to assess the real impact of socioeconomic and environmental factors in order to set up targeted campaigns against malaria at an accurate scale. Our goal was to detect malaria hotspots in rural area and assess the extent to which household socioeconomic status and meteorological recordings may explain the occurrence and evolution of these hotspots.

METHODS

Data on malaria cases from 2010 to 2014 and on socioeconomic and meteorological factors were acquired from four health facilities within the Nanoro demographic surveillance area. Statistical cross correlation was used to quantify the temporal association between weekly malaria incidence and meteorological factors. Local spatial autocorrelation analysis was performed and restricted to each transmission period using Kulldorff's elliptic spatial scan statistic. Univariate and multivariable analysis were used to assess the principal socioeconomic and meteorological determinants of malaria hotspots using a Generalized Estimating Equation (GEE) approach.

RESULTS

Rainfall and temperature were positively and significantly associated with malaria incidence, with a lag time of 9 and 14 weeks, respectively. Spatial analysis showed a spatial autocorrelation of malaria incidence and significant hotspots which was relatively stable throughout the study period. Furthermore, low socioeconomic status households were strongly associated with malaria hotspots (aOR = 1.21, 95% confidence interval: 1.03-1.40).

CONCLUSION

These fine-scale findings highlight a relatively stable spatio-temporal pattern of malaria risk and indicate that social and environmental factors play an important role in malaria incidence. Integrating data on these factors into existing malaria struggle tools would help in the development of sustainable bottleneck strategies adapted to the local context for malaria control.

Impact of mass drug administration campaigns depends on interaction with seasonal human movement

Background

Mass drug administration (MDA) is a control and elimination tool for treating infectious diseases. For malaria, it is widely accepted that conducting MDA during the dry season results in the best outcomes. However, seasonal movement of populations into and out of MDA target areas is common in many places and could potentially fundamentally limit the ability of MDA campaigns to achieve elimination.

Methods

A mathematical model was used to simulate malaria transmission in two villages connected to a high-risk area into and out of which 10% of villagers traveled seasonally. MDA was given only in the villages. Prevalence reduction under various possible timings of MDA and seasonal travel was predicted.

Results

MDA is most successful when distributed outside the traveling season and during the village low-transmission season. MDA is least successful when distributed during the traveling season and when traveling overlaps with the peak transmission season in the high-risk area. Mistiming MDA relative to seasonal travel resulted in much poorer outcomes than mistiming MDA relative to the peak transmission season within the villages.

Conclusions

Seasonal movement patterns of high-risk groups should be taken into consideration when selecting the optimum timing of MDA campaigns.

P. Lopes S, Fé NF, Lima JBP, Guerra MGB, Pimenta PFP, Bassat Q, Mueller I, Lacerda MVG, Monteiro WM. Use of anthropophilic culicid-based xenosurveillance as a proxy for Plasmodium vivax malaria burden and transmission hotspots identification

Vector-borne diseases account for more than 17% of all infectious diseases, causing more than one million deaths annually. Malaria remains one of the most important public health problems worldwide. These vectors are bloodsucking insects, which can transmit disease-producing microorganisms during a blood meal. The contact of culicids with human populations living in malaria-endemic areas suggests that the identification of Plasmodium genetic material in the blood present in the gut of these mosquitoes may be possible. The process of assessing the blood meal for the presence of pathogens is termed 'xenosurveillance'. In view of this, the present work investigated the relationship between the frequency with which Plasmodium DNA is found in culicids and the frequency with which individuals are found to be carrying malaria parasites. A cross-sectional study was performed in a peri-urban area of Manaus, in the Western Brazilian Amazon, by simultaneously collecting human blood samples and trapping culicids from households. A total of 875 individuals were included in the study and a total of 13,374mosquito specimens were captured. Malaria prevalence in the study area was 7.7%. The frequency of households with at least one culicid specimen carrying Plasmodium DNA was 6.4%. Plasmodium infection incidence was significantly related to whether any Plasmodium positive blood-fed culicid was found in the same household [IRR 3.49 (CI95% 1.38-8.84); p = 0.008] and for indoor-collected culicids [IRR 4.07 (CI95%1.25-13.24); p = 0.020]. Furthermore, the number of infected people in the house at the time of mosquito collection was related to whether there were any positive blood-fed culicid mosquitoes in that household for collection methods combined [IRR 4.48 (CI95%2.22-9.05); p<0.001] or only for indoor-collected culicids [IRR 4.88 (CI95%2.01-11.82); p<0.001]. Our results suggest that xenosurveillance can be used in endemic tropical regions in order to estimate the malaria burden and identify transmission foci in areas where Plasmodium vivax is predominant.