Human movement data for malaria control and elimination strategic planning

Spatiotemporal analysis of within-country imported malaria in Brazilian municipalities, 2004-2022

Human mobility has challenged malaria elimination efforts and remains difficult to routinely track. In Brazil, administrative records from the Ministry of Health allow monitoring of mobility locally and internationally. Although most imported malaria cases are between municipalities in Brazil, detailed knowledge of patterns of mobility is limited. Here, we address this gap by quantifying and describing patterns of malaria-infected individuals across the Amazon. We used network analysis, spatial clustering, and linear models to quantify and characterize the movement of malaria cases in Brazil between 2004 and 2022. We identified sources and sinks of malaria within and between states. We found that between-state movement of cases has become proportionally more important than within-state, that source clusters persisted longer than sink clusters, that movement of cases into sinks was seasonal while movement out of sources was not, and that importation is an impediment for subnational elimination in many municipalities. We elucidate the vast travel networks of malaria infected individuals that characterize the Amazon region. Uncovering patterns of malaria case mobility is vital for effective microstratification within Brazil. Our results have implications for intervention stratification across Brazil in line with the country's goal of malaria elimination by 2035.

Assessing the risk of malaria local transmission and re-introduction in China from pre-elimination to elimination: A systematic review

Assessing the risk of malaria local transmission and re-introduction is crucial for the preparation and implementation of an effective elimination campaign and the prevention of malaria re-introduction in China. Therefore, this review aims to evaluate the risk factors for malaria local transmission and re-introduction in China over the period of pre-elimination to elimination. Data were obtained from six databases searched for studies that assessed malaria local transmission risk before malaria elimination and re-introduction risk after the achievement of malaria elimination in China since the launch of the NMEP in 2010, employing the keywords "malaria" AND ("transmission" OR "re-introduction") and their synonyms. A total of 8,124 articles were screened and 53 articles describing 55 malaria risk assessment models in China from 2010 to 2023, including 40 models assessing malaria local transmission risk (72.7%) and 15 models assessing malaria re-introduction risk (27.3%). Factors incorporated in the 55 models were extracted and classified into six categories, including environmental and meteorological factors (39/55, 70.9%), historical epidemiology (35/55, 63.6%), vectorial factors (32/55, 58.2%), socio-demographic information (15/26, 53.8%), factors related to surveillance and response capacity (18/55, 32.7%), and population migration aspects (13/55, 23.6%). Environmental and meteorological factors as well as vectorial factors were most commonly incorporated in models assessing malaria local transmission risk (29/40, 72.5% and 21/40, 52.5%) and re-introduction risk (10/15, 66.7% and 11/15, 73.3%). Factors related to surveillance and response capacity and population migration were also important in malaria re-introduction risk models (9/15, 60%, and 6/15, 40.0%). A total of 18 models (18/55, 32.7%) reported the modeling performance. Only six models were validated internally and five models were validated externally. Of 53 incorporated studies, 45 studies had a quality assessment score of seven and above. Environmental and meteorological factors as well as vectorial factors play a significant role in malaria local transmission and re-introduction risk assessment. The factors related to surveillance and response capacity and population migration are more important in assessing malaria re-introduction risk. The internal and external validation of the existing models needs to be strengthened in future studies.

Human movement patterns of farmers and forest workers from the Thailand-Myanmar border

Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality among study participants. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.

Gaps in research and capacity development for malaria surveillance and response in the Asia-Pacific: meeting report

BACKGROUND

This report is based on the 2021 annual meeting of the Asia-Pacific Malaria Elimination Network Surveillance and Response Working Group held online on November 1-3, 2021. In light of the 2030 regional malaria elimination goal, there is an urgency for Asia-Pacific countries to accelerate progress towards national elimination and prevent re-establishment. The Asia Pacific Malaria Elimination Network (APMEN) Surveillance Response Working Group (SRWG) supports elimination goals of national malaria control programmes (NMCPs) by expanding the knowledge base, guiding the region-specific operational research agenda and addressing evidence gaps to improve surveillance and response activities.

METHODS

An online annual meeting was hosted from 1 to 3 November 2021, to reflect on research needed to support malaria elimination in the region, challenges with malaria data quality and integration, current surveillance-related technical tools, and training needs of NMCPs to support surveillance and response activities. Facilitator-led breakout groups were held during meeting sessions to encourage discussion and share experience. A list of identified research priorities was voted on by attendees and non-attending NMCP APMEN contacts.

FINDINGS

127 participants from 13 country partners and 44 partner institutions attended the meeting, identifying strategies to address malaria transmission amongst mobile and migrant populations as the top research priority, followed by cost effective surveillance strategies in low resource settings, and integration of malaria surveillance into broader health systems. Key challenges, solutions and best practices for improving data quality and integrating epidemiology and entomology data were identified, including technical solutions to improve surveillance activities, guiding priority themes for hosting informative webinars, training workshops and technical support initiatives. Inter-regional partnerships and SRWG-led training plans were developed in consultation with members to be launched from 2022 onwards.

CONCLUSION

The 2021 SRWG annual meeting provided an opportunity for regional stakeholders, both NMCPs and APMEN partner institutions, to highlight remaining challenges and barriers and identify research priorities pertaining to surveillance and response in the region, and advocate for strengthening capacity through training and supportive partnerships.

Livelihood activities, human mobility, and risk of malaria infection in elimination settings: a case-control study

BACKGROUND

Livelihood activities and human movements participate in the epidemiology of vector-borne diseases and influence malaria risk in elimination settings. In Saudi Arabia, where malaria transmission intensity varies geographically, it is vital to understand the components driving transmission within specific areas. In addition, shared social, behavioural, and occupational characteristics within communities may provoke the risk of malaria infection. This study aims to understand the relationship between human mobility, livelihood activities, and the risk of malaria infection in the border region of Jazan to facilitate further strategic malaria interventions. In addition, the study will complement and reinforce the existing efforts to eliminate malaria on the Saudi and Yemen border by providing a deeper understanding of human movement and livelihood activities.

METHODS

An unmatched case-control study was conducted. A total of 261 participants were recruited for the study, including 81 cases of confirmed malaria through rapid diagnostic tests (RDTs) and microscopy and 180 controls in the Baish Governorate in Jazan Provinces, Saudi Arabia. Individuals who received malaria tests were interviewed regarding their livelihood activities and recent movement (travel history). A questionnaire was administered, and the data was captured electronically. STATA software version 16 was used to analyse the data. Bivariate and multivariate analyses were conducted to determine if engaging in agricultural activities such as farming and animal husbandry, recent travel history outside of the home village within the last 30 days and participating in spiritual gatherings were related to malaria infection status.

RESULTS

A logistical regression model was used to investigate components associated with malaria infection. After adjusting several confounding factors, individuals who reported travelling away from their home village in the last 30 days OR 11.5 (95% CI 4.43-29.9), and those who attended a seasonal night spiritual gathering OR 3.04 (95% CI 1.10-8.42), involved in animal husbandry OR 2.52 (95% CI 1.10-5.82), and identified as male OR 4.57 (95% CI 1.43-14.7), were more likely to test positive for malaria infection.

CONCLUSION

Human movement and livelihood activities, especially at nighttime, should be considered malaria risk factors in malaria elimination settings, mainly when the targeted area is limited to a confined borderland area.

Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model

BACKGROUND

More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multiagent mobility simulation model was built to simulate the movements of villagers between home and their workplaces in 2 townships in Myanmar.

METHODS

An agent-based model (ABM) was built to simulate daily travel to and from work based on responses to a travel survey. Key elements for the ABM were land cover, travel time, travel mode, occupation, malaria prevalence, and a detailed road network. Most visited network segments for different occupations and for malaria-positive cases were extracted and compared. Data from a separate survey were used to validate the simulation.

RESULTS

Mobility characteristics for different occupation groups showed that while certain patterns were shared among some groups, there were also patterns that were unique to an occupation group. Forest workers were estimated to be the most mobile occupation group, and also had the highest potential malaria exposure associated with their daily travel in Ann Township. In Singu Township, forest workers were not the most mobile group; however, they were estimated to visit regions that had higher prevalence of malaria infection over other occupation groups.

CONCLUSIONS

Using an ABM to simulate daily travel generated mobility patterns for different occupation groups. These spatial patterns varied by occupation. Our simulation identified occupations at a higher risk of being exposed to malaria and where these exposures were more likely to occur.

Characterizing human movement patterns using GPS data loggers in an area of persistent malaria in Zimbabwe along the Mozambique border

BACKGROUND

Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions.

METHODS

A study was conducted in Mutasa District, Zimbabwe, to investigate human movement patterns in an area of persistent transmission along the Mozambique border. Over 1 year, a convenience sample of 20 participants/month was recruited from active malaria surveillance cohorts to carry an IgotU^® GT-600 global positioning system (GPS) data logger during all daily activities. Consenting participants were tested for malaria at data logger distribution using rapid antigen diagnostic tests and completed a survey questionnaire. GPS data were analyzed using a trajectory analysis tool, and participant movement patterns were characterized throughout the study area and across the border into Mozambique using movement intensity maps, activity space plots, and statistical analyses.

RESULTS

From June 2016-May 2017, 184 participants provided movement tracks encompassing > 350,000 data points and nearly 8000 person-days. Malaria prevalence at logger distribution was 3.7%. Participants traveled a median of 2.8 km/day and spent a median of 4.6 h/day away from home. Movement was widespread within and outside the study area, with participants traveling up to 500 km from their homes. Indices of mobility were higher in the dry season than the rainy season (median km traveled/day = 3.5 vs. 2.2, P = 0.03), among male compared to female participants (median km traveled/day = 3.8 vs. 2.0, P = 0.0008), and among adults compared to adolescents (median total km traveled = 104.6 vs. 59.5, P = 0.05). Half of participants traveled outside the study area, and 30% traveled into Mozambique, including 15 who stayed in Mozambique overnight.

CONCLUSIONS

Study participants in Mutasa District, Zimbabwe, were highly mobile throughout the year. Many participants traveled long distances from home, including overnight trips into Mozambique, with clear implications for malaria control. Interventions targeted at mobile populations and cross-border transmission may be effective in preventing malaria introductions in this region.

Human and vector behaviors determine exposure to Anopheles in Namibia

Background

Although the Republic of Namibia has significantly reduced malaria transmission, regular outbreaks and persistent transmission impede progress towards elimination. Towards an understanding of the protective efficacy, as well as gaps in protection, associated with long-lasting insecticidal nets (LLINs), human and Anopheles behaviors were evaluated in parallel in three malaria endemic regions, Kavango East, Ohangwena and Zambezi, using the Entomological Surveillance Planning Tool to answer the question: where and when are humans being exposed to bites of Anopheles mosquitoes?

Methods

Surveillance activities were conducted during the malaria transmission season in March 2018 for eight consecutive nights. Four sentinel structures per site were selected, and human landing catches and human behavior observations were consented to for a total of 32 collection nights per site. The selected structures were representative of local constructions (with respect to building materials and size) and were at least 100 m from each other. For each house where human landing catches were undertaken, a two-person team collected mosquitoes from 1800 to 0600 hours.

Results

Surveillance revealed the presence of the primary vectors Anopheles arabiensis, Anopheles gambiae sensu stricto (s.s.) and Anopheles funestus s.s., along with secondary vectors (Anopheles coustani sensu lato and Anopheles squamosus), with both indoor and outdoor biting behaviors based on the site. Site-specific human behaviors considerably increased human exposure to vector biting. The interaction between local human behaviors (spatial and temporal presence alongside LLIN use) and vector behaviors (spatial and temporal host seeking), and also species composition, dictated where and when exposure to infectious bites occurred, and showed that exposure was primarily indoors in Kavango East (78.6%) and outdoors in Ohangwena (66.7%) and Zambezi (81.4%). Human behavior-adjusted exposure was significantly different from raw vector biting rate.

Conclusions

Increased LLIN use may significantly increase protection and reduce exposure to malaria, but may not be enough to eliminate the disease, as gaps in protection will remain both indoors (when people are awake and not using LLINs) and outdoors. Alternative interventions are required to address these exposure gaps. Focused and question-based operational entomological surveillance together with human behavioral observations may considerably improve our understanding of transmission dynamics as well as intervention efficacy and gaps in protection.

Graphical Abstract

Mobile phone handover data for measuring and analysing human population mobility in Western Ethiopia: implication for malaria disease epidemiology and elimination efforts

BACKGROUND

Human mobility behaviour modelling plays an essential role in the understanding and control of the spread of contagious diseases by limiting the contact among individuals, predicting the spatio-temporal evolution of an epidemic and inferring migration patterns. It informs programmatic and policy decisions for effective and efficient intervention. The objective of this research is to assess the human mobility pattern and analyse its implication for malaria disease epidemiology.

METHODS

In this study, human mobility patterns in Benishangul-Gumuz and Gambella regions in Western Ethiopia were explored based on a cellular network mobility parameter (e.g., handover rate) via real world data. Anonymized data were retrieved for mobile active users with mobility related information. The data came from anonymous traffic records collected from all the study areas. For each cell, the necessary mobility parameter data per hour, week and month were collected. A scale factor was computed to change the mobility parameter value to the human mobility pattern. Finally, the relative human mobility probability for each scenario was estimated. MapInfo and Matlab softwares were used for visualization and analysis purposes. Hourly travel patterns in the study settings were compared with hourly malaria mosquito vector feeding behaviour.

RESULTS

Heterogeneous human movement patterns were observed in the two regions with some areas showing typically high human mobility. Furthermore, the number of people entering into the two study regions was high during the highest malaria transmission season. Two peaks of hourly human movement, 8:00 to 9:00 and 16:00 to 18:00, emerged in Benishangul-Gumuz region while 8:00 to 10:00 and 16:00 to 18:00 were the peak hourly human mobility time periods in Gambella region. The high human movement in the night especially before midnight in the two regions may increase the risk of getting mosquito bite particularly by early biters depending on malaria linked human behaviour of the population.

CONCLUSIONS

High human mobility was observed both within and outside the two regions. The population influx and efflux in these two regions is considerably high. This may specifically challenge the transition from malaria control to elimination. The daily mobility pattern is worth considering in the context of malaria transmission. In line with this malaria related behavioural patterns of humans need to be properly addressed.

Effect of out-of-village working activities on recent malaria exposure in the Peruvian Amazon using parametric g-formula

In the Amazon Region of Peru, occupational activities are important drivers of human mobility and may increase the individual risk of being infected while contributing to increasing malaria community-level transmission. Even though out-of-village working activities and other mobility patterns have been identified as determinants of malaria transmission, no studies have quantified the effect of out-of-village working activities on recent malaria exposure and proposed plausible intervention scenarios. Using two population-based cross-sectional studies in the Loreto Department in Peru, and the parametric g-formula method, we simulated various hypothetical scenarios intervening in out-of-village working activities to reflect their potential health benefits. This study estimated that the standardized mean outcome (malaria seroprevalence) in the unexposed population (no out-of-village workers) was 44.6% (95% CI: 41.7%-47.5%) and 66.7% (95% CI: 61.6%-71.8%) in the exposed population resulting in a risk difference of 22.1% (95% CI: 16.3%-27.9%). However, heterogeneous patterns in the effects of interest were observed between peri-urban and rural areas (Cochran's Q test = 15.5, p < 0.001). Heterogeneous patterns were also observed in scenarios of increased prevalence of out-of-village working activities and restriction scenarios by gender (male vs. female) and age (18 and under vs. 19 and older) that inform possible occupational interventions targetting population subgroups. The findings of this study support the hypothesis that targeting out-of-village workers will considerably benefit current malaria elimination strategies in the Amazon Region. Particularly, males and adult populations that carried out out-of-village working activities in rural areas contribute the most to the malaria seropositivity (recent exposure to the parasite) in the Peruvian Amazon.

Global Cross-Border Malaria Control Collaborative Initiatives: A Scoping Review

Malaria remains a global disease of public health concern. Malaria control collaborative initiatives are widely being adopted to reduce malaria burden by various countries. This review sought to describe current and past cross-border malaria control initiatives focusing on key activities, outcomes and challenges. An exhaustive search was conducted in Web of Science, PubMed, Google Scholar and EBSCOhost using the following key words: cross-border malaria control, cross-border malaria elimination, bi-national malaria control and multinational malaria control, in combination with Boolean operators "AND" and "OR". Eleven studies satisfied the inclusion criteria for this review. The majority of collaborative initiatives have been formed within regional developmental and continental bodies with support from political leadership. The studies revealed that joint vector control, cases management, epidemiological data sharing along border regions as well as resource sharing and capacity building are some of the key collaborative initiatives being implemented globally. Collaborative initiatives have led to significant reduction in malaria burden and mortality. The majority of collaborative initiatives are underfunded and rely on donor support. We concluded that cross-border malaria collaborative initiatives have the capacity to reduce malaria burden and mortality along border regions; however, inadequate internal funding and over-reliance on donor funding remain the biggest threats to the survival of collaborative initiatives.

Relating Eulerian and Lagrangian spatial models for vector-host disease dynamics through a fundamental matrix

We explore the relationship between Eulerian and Lagrangian approaches for modeling movement in vector-borne diseases for discrete space. In the Eulerian approach we account for the movement of hosts explicitly through movement rates captured by a graph Laplacian matrix L. In the Lagrangian approach we only account for the proportion of time that individuals spend in foreign patches through a mixing matrix P. We establish a relationship between an Eulerian model and a Lagrangian model for the hosts in terms of the matrices L and P. We say that the two modeling frameworks are consistent if for a given matrix P, the matrix L can be chosen so that the residence times of the matrix P and the matrix L match. We find a sufficient condition for consistency, and examine disease quantities such as the final outbreak size and basic reproduction number in both the consistent and inconsistent cases. In the special case of a two-patch model, we observe how similar values for the basic reproduction number and final outbreak size can occur even in the inconsistent case. However, there are scenarios where the final sizes in both approaches can significantly differ by means of the relationship we propose.

Surveillance to achieve malaria elimination in eastern Myanmar: a 7-year observational study

Background

The collection and utilization of surveillance data is essential in monitoring progress towards achieving malaria elimination, in the timely response to increases in malaria case numbers and in the assessment of programme functioning. This paper describes the surveillance activities used by the malaria elimination task force (METF) programme which operates in eastern Myanmar, and provides an analysis of data collected from weekly surveillance, case investigations, and monitoring and evaluation of programme performance.

Methods

This retrospective analysis was conducted using data collected from a network of 1250 malaria posts operational between 2014 and 2021. To investigate changes in data completeness, malaria post performance, malaria case numbers, and the demographic details of malaria cases, summary statistics were used to compare data collected over space and time.

Results

In the first 3 years of the METF programme, improvements in data transmission routes resulted in a 18.9% reduction in late reporting, allowing for near real-time analysis of data collected at the malaria posts. In 2020, travel restrictions were in place across Karen State in response to COVID-19, and from February 2021 the military coup in Myanmar resulted in widescale population displacement. However, over that period there has been no decline in malaria post attendance, and the majority of consultations continue to occur within 48 h of fever onset. Case investigations found that 43.8% of cases travelled away from their resident village in the 3 weeks prior to diagnosis and 36.3% reported never using a bed net whilst sleeping in their resident village, which increased to 72.2% when sleeping away from their resident village. Malaria post assessments performed in 82.3% of the METF malaria posts found malaria posts generally performed to a high standard.

Conclusions

Surveillance data collected by the METF programme demonstrate that despite significant changes in the context in which the programme operates, malaria posts have remained accessible and continue to provide early diagnosis and treatment contributing to an 89.3% decrease in Plasmodium falciparum incidence between 2014 and 2021.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04175-w.

Epidemiology of the zoonotic malaria Plasmodium knowlesi in changing landscapes

Within the past two decades, incidence of human cases of the zoonotic malaria Plasmodium knowlesi has increased markedly. P. knowlesi is now the most common cause of human malaria in Malaysia and threatens to undermine malaria control programmes across Southeast Asia. The emergence of zoonotic malaria corresponds to a period of rapid deforestation within this region. These environmental changes impact the distribution and behaviour of the simian hosts, mosquito vector species and human populations, creating new opportunities for P. knowlesi transmission. Here, we review how landscape changes can drive zoonotic disease emergence, examine the extent and causes of these changes across Southeast and identify how these mechanisms may be impacting P. knowlesi dynamics. We review the current spatial epidemiology of reported P. knowlesi infections in people and assess how these demographic and environmental changes may lead to changes in transmission patterns. Finally, we identify opportunities to improve P. knowlesi surveillance and develop targeted ecological interventions within these landscapes.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics

Individual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer transmission dynamics, in conjunction with additional information such as symptom onset time and genetic distance. However, in the absence of data about the flow of parasites between populations, the spatial scale of malaria transmission is often not clear. As a result, it is important to understand the impact of varying assumptions about the spatial scale of transmission on key metrics of malaria transmission, such as reproduction numbers. We developed a method which allows the flexible integration of distance metrics (such as Euclidian distance, genetic distance or accessibility matrices) with temporal information into a single inference framework to infer malaria reproduction numbers. Twelve scenarios were defined, representing different assumptions about the likelihood of transmission occurring over different geographic distances and likelihood of missing infections (as well as high and low amounts of uncertainty in this estimate). These scenarios were applied to four individual level datasets from malaria eliminating contexts to estimate individual reproduction numbers and how they varied over space and time. Model comparison suggested that including spatial information improved models as measured by second order AIC (ΔAICc), compared to time only results. Across scenarios and across datasets, including spatial information tended to increase the seasonality of temporal patterns in reproduction numbers and reduced noise in the temporal distribution of reproduction numbers. The best performing parameterisations assumed long-range transmission (> 200 km) was possible. Our approach is flexible and provides the potential to incorporate other sources of information which can be converted into distance or adjacency matrices such as travel times or molecular markers.

Analysing human population movement data for malaria control and elimination

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Human movement patterns of farmers and forest workers from the Thailand-Myanmar border

Background: Human travel patterns play an important role in infectious disease epidemiology and ecology. Movement into geographic spaces with high transmission can lead to increased risk of acquiring infections. Pathogens can also be distributed across the landscape via human travel. Most fine scale studies of human travel patterns have been done in urban settings in wealthy nations. Research into human travel patterns in rural areas of low- and middle-income nations are useful for understanding the human components of epidemiological systems for malaria or other diseases of the rural poor. The goal of this research was to assess the feasibility of using GPS loggers to empirically measure human travel patterns in this setting, as well as to quantify differing travel patterns by age, gender, and seasonality. Methods: In this pilot study we recruited 50 rural villagers from along the Myanmar-Thailand border to carry GPS loggers for the duration of a year. The GPS loggers were programmed to take a time-stamped reading every 30 minutes. We calculated daily movement ranges and multi-day trips by age and gender. We incorporated remote sensing data to assess patterns of days and nights spent in forested or farm areas, also by age and gender. Results: Our study showed that it is feasible to use GPS devices to measure travel patterns, though we had difficulty recruiting women and management of the project was relatively intensive. We found that older adults traveled farther distances than younger adults and adult males spent more nights in farms or forests. Conclusion: The results of this study suggest that further work along these lines would be feasible in this region. Furthermore, the results from this study are useful for individual-based models of disease transmission and land use.

Using mobile phone data to reveal risk flow networks underlying the HIV epidemic in Namibia

Twenty-six million people are living with HIV in sub-Saharan Africa; epidemics are widely dispersed, due to high levels of mobility. However, global elimination strategies do not consider mobility. We use Call Detail Records from 9 billion calls/texts to model mobility in Namibia; we quantify the epidemic-level impact by using a mathematical framework based on spatial networks. We find complex networks of risk flows dispersed risk countrywide: increasing the risk of acquiring HIV in some areas, decreasing it in others. Overall, 40% of risk was mobility-driven. Networks contained multiple risk hubs. All constituencies (administrative units) imported and exported risk, to varying degrees. A few exported very high levels of risk: their residents infected many residents of other constituencies. Notably, prevalence in the constituency exporting the most risk was below average. Large-scale networks of mobility-driven risk flows underlie generalized HIV epidemics in sub-Saharan Africa. In order to eliminate HIV, it is likely to become increasingly important to implement innovative control strategies that focus on disrupting risk flows.

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

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

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

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

Using a participatory qualitative risk assessment to estimate the risk of introduction and spread of transboundary animal diseases in scarce-data environments: A Spatial Qualitative Risk Analysis applied to foot-and-mouth disease in Tunisia 2014-2019

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

Improving National Intelligence for Public Health Preparedness: a methodological approach to finding local multi-sector indicators for health security

The COVID-19 epidemic is the latest evidence of critical gaps in our collective ability to monitor country-level preparedness for health emergencies. The global frameworks that exist to strengthen core public health capacities lack coverage of several preparedness domains and do not provide mechanisms to interface with local intelligence. We designed and piloted a process, in collaboration with three National Public Health Institutes (NPHIs) in Ethiopia, Nigeria and Pakistan, to identify potential preparedness indicators that exist in a myriad of frameworks and tools in varying local institutions. Following a desk-based systematic search and expert consultations, indicators were extracted from existing national and subnational health security-relevant frameworks and prioritised in a multi-stakeholder two-round Delphi process. Eighty-six indicators in Ethiopia, 87 indicators in Nigeria and 51 indicators in Pakistan were assessed to be valid, relevant and feasible. From these, 14–16 indicators were prioritised in each of the three countries for consideration in monitoring and evaluation tools. Priority indicators consistently included private sector metrics, subnational capacities, availability and capacity for electronic surveillance, measures of timeliness for routine reporting, data quality scores and data related to internally displaced persons and returnees. NPHIs play an increasingly central role in health security and must have access to data needed to identify and respond rapidly to public health threats. Collecting and collating local sources of information may prove essential to addressing gaps; it is a necessary step towards improving preparedness and strengthening international health regulations compliance.

The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology

The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making.

Open-Source 3D Printable GPS Tracker to Characterize the Role of Human Population Movement on Malaria Epidemiology in River Networks: A Proof-of-Concept Study in the Peruvian Amazon

Human movement affects malaria epidemiology at multiple geographical levels; however, few studies measure the role of human movement in the Amazon Region due to the challenging conditions and cost of movement tracking technologies. We developed an open-source low-cost 3D printable GPS-tracker and used this technology in a cohort study to characterize the role of human population movement in malaria epidemiology in a rural riverine village in the Peruvian Amazon. In this pilot study of 20 participants (mean age = 40 years old), 45,980 GPS coordinates were recorded over 1 month. Characteristic movement patterns were observed relative to the infection status and occupation of the participants. Applying two analytical animal movement ecology methods, utilization distributions (UDs) and integrated step selection functions (iSSF), we showed contrasting environmental selection and space use patterns according to infection status. These data suggested an important role of human movement in the epidemiology of malaria in the Peruvian Amazon due to high connectivity between villages of the same riverine network, suggesting limitations of current community-based control strategies. We additionally demonstrate the utility of this low-cost technology with movement ecology analysis to characterize human movement in resource-poor environments.

Assessing the impact of coordinated COVID-19 exit strategies across Europe

As rates of new coronavirus disease 2019 (COVID-19) cases decline across Europe owing to nonpharmaceutical interventions such as social distancing policies and lockdown measures, countries require guidance on how to ease restrictions while minimizing the risk of resurgent outbreaks. We use mobility and case data to quantify how coordinated exit strategies could delay continental resurgence and limit community transmission of COVID-19. We find that a resurgent continental epidemic could occur as many as 5 weeks earlier when well-connected countries with stringent existing interventions end their interventions prematurely. Further, we find that appropriate coordination can greatly improve the likelihood of eliminating community transmission throughout Europe. In particular, synchronizing intermittent lockdowns across Europe means that half as many lockdown periods would be required to end continent-wide community transmission.

Inference and prediction of malaria transmission dynamics using time series data

BACKGROUND

Disease surveillance systems are essential for effective disease intervention and control by monitoring disease prevalence as time series. To evaluate the severity of an epidemic, statistical methods are widely used to forecast the trend, seasonality, and the possible number of infections of a disease. However, most statistical methods are limited in revealing the underlying dynamics of disease transmission, which may be affected by various impact factors, such as environmental, meteorological, and physiological factors. In this study, we focus on investigating malaria transmission dynamics based on time series data.

METHODS

A data-driven nonlinear stochastic model is proposed to infer and predict the dynamics of malaria transmission based on the time series of prevalence data. Specifically, the dynamics of malaria transmission is modeled based on the notion of vectorial capacity (VCAP) and entomological inoculation rate (EIR). A particle Markov chain Monte Carlo (PMCMC) method is employed to estimate the model parameters. Accordingly, a one-step-ahead prediction method is proposed to project the number of future malaria infections. Finally, two case studies are carried out on the inference and prediction of Plasmodium vivax transmission in Tengchong and Longling, Yunnan province, China.

RESULTS

The results show that the trained data-driven stochastic model can well fit the historical time series of P. vivax prevalence data in both counties from 2007 to 2010. Moreover, with well-trained model parameters, the proposed one-step-ahead prediction method can achieve better performances than that of the seasonal autoregressive integrated moving average model with respect to predicting the number of future malaria infections.

CONCLUSIONS

By involving dynamically changing impact factors, the proposed data-driven model together with the PMCMC method can successfully (i) depict the dynamics of malaria transmission, and (ii) achieve accurate one-step-ahead prediction about malaria infections. Such a data-driven method has the potential to investigate malaria transmission dynamics in other malaria-endemic countries/regions.

Protecting the peri-domestic environment: the challenge for eliminating residual malaria

Malaria transmission after universal access and use of malaria preventive services is known as residual malaria transmission. The concurrent spatial-temporal distributions of people and biting mosquitoes in malaria endemic villages determines where and when residual malaria transmission occurs. Understanding human and vector population behaviors and movements is a critical first step to prevent mosquito bites to eliminate residual malaria transmission. This study identified where people in the Solomon Islands are over 24-hour periods. Participants (59%) were predominantly around the house but not in their house when most biting by Anopheles farauti, the dominant malaria vector, occurs. While 84% of people slept under a long-lasting insecticide-treated bed net (LLIN), on average only 7% were under an LLIN during the 18:00 to 21:00 h peak mosquito biting period. On average, 34% of participants spend at least one night away from their homes each fortnight. Despite high LLIN use while sleeping, most human biting by An. farauti occurs early in the evening before people go to sleep when people are in peri-domestic areas (predominantly on verandas or in kitchen areas). Novel vector control tools that protect individuals from mosquito bites between sundown and when people sleep are needed for peri-domestic areas.

Determinants of MDA impact and designing MDAs towards malaria elimination

Malaria remains at the forefront of scientific research and global political and funding agendas. Malaria models have consistently oversimplified how mass interventions are implemented. Here, we present an individual based, spatially explicit model of P. falciparum malaria transmission that includes all the programmatic implementation details of mass drug administration (MDA) campaigns. We uncover how the impact of MDA campaigns is determined by the interaction between implementation logistics, patterns of human mobility and how transmission risk is distributed over space. Our results indicate that malaria elimination is only realistically achievable in settings with very low prevalence and can be hindered by spatial heterogeneities in risk. In highly mobile populations, accelerating MDA implementation increases likelihood of elimination; if populations are more static, deploying less teams would be cost optimal. We conclude that mass drug interventions can be an invaluable tool towards malaria elimination in low endemicity areas, specifically when paired with effective vector control.

Mapping the travel patterns of people with malaria in Bangladesh

BACKGROUND

Spread of malaria and antimalarial resistance through human movement present major threats to current goals to eliminate the disease. Bordering the Greater Mekong Subregion, southeast Bangladesh is a potentially important route of spread to India and beyond, but information on travel patterns in this area are lacking.

METHODS

Using a standardised short survey tool, 2090 patients with malaria were interviewed at 57 study sites in 2015-2016 about their demographics and travel patterns in the preceding 2 months.

RESULTS

Most travel was in the south of the study region between Cox's Bazar district (coastal region) to forested areas in Bandarban (31% by days and 45% by nights), forming a source-sink route. Less than 1% of travel reported was between the north and south forested areas of the study area. Farmers (21%) and students (19%) were the top two occupations recorded, with 67 and 47% reporting travel to the forest respectively. Males aged 25-49 years accounted for 43% of cases visiting forests but only 24% of the study population. Children did not travel. Women, forest dwellers and farmers did not travel beyond union boundaries. Military personnel travelled the furthest especially to remote forested areas.

CONCLUSIONS

The approach demonstrated here provides a framework for identifying key traveller groups and their origins and destinations of travel in combination with knowledge of local epidemiology to inform malaria control and elimination efforts. Working with the NMEP, the findings were used to derive a set of policy recommendations to guide targeting of interventions for elimination.

Analysis of anti-Plasmodium IgG profiles among Fulani nomadic pastoralists in northern Senegal to assess malaria exposure

BACKGROUND

Northern Senegal is a zone of very low malaria transmission, with an annual incidence of < 5/1000 inhabitants. This area, where the Senegal National Malaria Control Programme has initiated elimination activities, hosts Fulani, nomadic, pastoralists that spend the dry season in the south where malaria incidence is higher (150-450/1000 inhabitants) and return to the north with the first rains. Previous research demonstrated parasite prevalence of < 1% in this Fulani population upon return from the south, similar to that documented in the north in cross-sectional surveys.

METHODS

A modified snowball sampling survey of nomadic pastoralists was conducted in five districts in northern Senegal during September and October 2014. Demographic information and dried blood spots were collected. Multiplex bead-based assays were used to assess antibody responses to merozoite surface protein (MSP-1₁₉) antigen of the four primary Plasmodium species, as well as circumsporozoite protein (CSP) and liver stage antigen (LSA-1) of Plasmodium falciparum.

RESULTS

In the five study districts, 1472 individuals were enrolled, with a median age of 22 years (range 1 to 80 years). Thirty-two percent of subjects were under 14 years and 57% were male. The overall seroprevalence of P. falciparum MSP-1₁₉, CSP and LSA-1 antibodies were 45, 12 and 5%, respectively. Plasmodium falciparum MSP-1₁₉ antibody responses increased significantly with age in all study areas, and were significantly higher among males. The highest seroprevalence to P. falciparum antigens was observed in the Kanel district (63%) and the lowest observed in Podor (28%). Low seroprevalence was observed for non-falciparum species in all the study sites: 0.4, 0.7 and 1.8%, respectively, for Plasmodium ovale, Plasmodium vivax and Plasmodium malariae MSP-1. Antibody responses to P. vivax were observed in all study sites except Kanel.

CONCLUSION

Prevalence of P. falciparum MSP-1₁₉ antibodies and increases by study participant age provided data for low levels of exposure among this transient nomadic population. In addition, antibody responses to P. falciparum short half-life markers (CSP and LSA-1) and non-falciparum species were low. Further investigations are needed to understand the exposure of the Fulani population to P. vivax.

A Crisis of Opportunity: Market-Making, Big Data, and the Consolidation of Migration as Risk

Crisis narratives surrounding Europe's 2015 migration influx fuelled demands for new ways of tracking, mapping and predicting human mobility. We explore how market opportunities for technology firms and data analytics start-ups created by the EU's Global Approach to Migration led to solutionistic approaches to compiling and analysing migration statistics. We show that initiatives such as the rebranding of existing platforms and services as migration prediction systems are consolidating policy conceptualisations of migration as risk. Despite the promise of greater granularity, this "big data approach" cannot offer greater certainty about who is on the move and why. Instead such approaches are ill-suited to understanding the complex dynamics of migration and to offering protection to vulnerable people. The marketisation of migration statistics through big data offers a key case for advancing progressive approaches to both migration statistics and global data justice.

Characterising malaria connectivity using malaria indicator survey data

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

Investigating the drivers of the spatio-temporal patterns of genetic differences between Plasmodium falciparum malaria infections in Kilifi County, Kenya

Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.4 km (95% CI 0.24, 1.20), for a distribution with 58% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes.

Microsatellite analysis reveals connectivity among geographically distant transmission zones of Plasmodium vivax in the Peruvian Amazon: A critical barrier to regional malaria elimination

Despite efforts made over decades by the Peruvian government to eliminate malaria, Plasmodium vivax remains a challenge for public health decision-makers in the country. The uneven distribution of its incidence, plus its complex pattern of dispersion, has made ineffective control measures based on global information that lack the necessary detail to understand transmission fully. In this sense, population genetic tools can complement current surveillance. This study describes the genetic diversity and population structure from September 2012 to March 2015 in three geographically distant settlements, Cahuide (CAH), Lupuna (LUP) and Santa Emilia (STE), located in the Peruvian Amazon. A total 777 P. vivax mono-infections, out of 3264, were genotyped. Among study areas, LUP showed 19.7% of polyclonal infections, and its genetic diversity (H_exp) was 0.544. Temporal analysis showed a significant increment of polyclonal infections and H_exp, and the introduction and persistence of a new parasite population since March 2013. In STE, 40.1% of infections were polyclonal, with H_exp = 0.596. The presence of four genetic clusters without signals of clonal expansion and infections with lower parasite densities compared against the other two areas were also found. At least four parasite populations were present in CAH in 2012, where, after June 2014, malaria cases decreased from 213 to 61, concomitant with a decrease in polyclonal infections (from 0.286 to 0.18), and expectedly variable H_exp. Strong signals of gene flow were present in the study areas and wide geographic distribution of highly diverse parasite populations were found. This study suggests that movement of malaria parasites by human reservoirs connects geographically distant malaria transmission areas in the Peruvian Amazon. The maintenance of high levels of parasite genetic diversity through human mobility is a critical barrier to malaria elimination in this region.

Plasmodium vivax transmission is heterogeneous and discontinuous in the Peruvian Amazon. Such heterogeneity is the result of factors that include, but are not restricted to, the environment, public policies, and characteristics of the parasite, the vector, and human activities. All these factors make P. vivax transmission resilient to interventions. In order to achieve the goals of control and local elimination, P. vivax surveillance must inform how those factors sustain disease transmission in order to focalize and synchronize control strategies. In this study, we implemented molecular surveillance complemented with population genetic tools in the areas of Cahuide, Lupuna, and Santa Emilia located in the Peruvian Amazon. In particular, we characterize the transmission and the parasite genetic variation in these sites from September 2012 to March 2015. The changes in parasite diversity, the wide geographic dispersion of parasite subpopulation and the introduction of a new parasite clone or subpopulation in Lupuna documented in this study suggest that connectivity among the different endemic areas, likely due to human mobility, sustains disease transmission in the region hindering the success of control measures. This information must be considered in the design of current control strategies.

Local human movement patterns and land use impact exposure to zoonotic malaria in Malaysian Borneo

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement and space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges.

Human population movement can impede the elimination of soil-transmitted helminth transmission in regions with heterogeneity in mass drug administration coverage and transmission potential between villages: a metapopulation analysis

BACKGROUND

Soil-transmitted helminth (STH) infections affect predominantly socio-economically disadvantaged populations in sub-Saharan Africa, East Asia and the Americas. Previous mathematical modelling studies have evaluated optimal intervention strategies to break STH transmission in clusters of villages. These studies assumed that villages are closed independent units with no movement of people in or out of communities. Here we examine how human population movement, for example, of seasonal migrant labourers, affect the outcome of mass drug administration (MDA) programmes.

RESULTS

We used a stochastic individual-based metapopulation model to analyse the impact of human population movement at varying rates on STH elimination efforts. Specifically, we looked at seasonal clumped movement events of infected individuals into a village. We showed that even if on average 75% of the entire resident population within a village are treated, an annual rate of 2-3% of the population arriving from an untreated source village can reduce the probability of STH elimination to less than 50% in high-prevalence settings. If a village is infection-free, an annual movement rate of 2-3% from an infected source village imposes a risk of re-introduction of STH of 75% or higher, unless the prevalence in the source village is less than 20%. Even a single arrival of 2-3% of the population can impose a risk of re-introducing STH of 50% or greater depending on the prevalence in the source village. The risk of re-introduction also depends on both the age group of moving individuals and STH species, since the pattern of cross-sectional age-prevalence and age-intensity profiles of infection in the human host are species-specific.

CONCLUSIONS

Planning for STH elimination programmes should account for human mobility patterns in defined regions. We recommend that individuals arriving from areas with ongoing STH transmission should receive preventive chemotherapy for STHs. This can most easily be implemented if migration is seasonal and overlaps with treatment rounds, e.g. seasonal migrant labour. Moreover, transmission hotspots in or near treatment clusters should be eliminated, for example, by implementing appropriate water, sanitation and hygiene (WASH) measures and targeting treatment to individuals living in hotspots.

The use of GPS data loggers to describe the impact of spatio-temporal movement patterns on malaria control in a high-transmission area of northern Zambia

Background

Human movement is a driver of malaria transmission and has implications for sustainable malaria control. However, little research has been done on the impact of fine-scale movement on malaria transmission and control in high-transmission settings. As interest in targeted malaria control increases, evaluations are needed to determine the appropriateness of these strategies in the context of human mobility across a variety of transmission settings.

Methods

A human mobility study was conducted in Nchelenge District, a high-transmission setting in northern Zambia. Over 1 year, 84 participants were recruited from active malaria surveillance cohorts to wear a global positioning system data logger for 1 month during all daily activity. Participants completed a survey questionnaire and underwent malaria testing and treatment at the time of logger distribution and at collection 1 month later. Incident malaria infections were identified using polymerase chain reaction. Participant movement was characterized throughout the study area and across areas targeted for an indoor residual spraying (IRS) intervention. Participant movement patterns were compared using movement intensity maps, activity space plots, and statistical analyses. Malaria risk was characterized across participants using spatial risk maps and time spent away from home during peak vector biting hours.

Results

Movement data were collected from 82 participants, and 63 completed a second study visit. Participants exhibited diverse mobility patterns across the study area, including movement into and out of areas targeted for IRS, potentially mitigating the impact of IRS on parasite prevalence. Movement patterns did not differ significantly by season or age, but male participants traveled longer distances and spent more time away from home. Monthly malaria incidence was 22%, and malaria risk was characterized as high across participants. Participants with incident parasitemia traveled a shorter distance and spent more time away from home during peak biting hours; however, these relationships were not statistically significant, and malaria risk score did not differ by incident parasitemia.

Conclusions

Individual movement patterns in Nchelenge District, Zambia have implications for malaria control, particularly the effectiveness of targeted IRS strategies. Large and fine-scale population mobility patterns should be considered when planning intervention strategies across transmission settings.

Electronic supplementary material

The online version of this article (10.1186/s12942-019-0183-y) contains supplementary material, which is available to authorized users.

Mass Drug Administration With Dihydroartemisinin-piperaquine and Malaria Transmission Dynamics in The Gambia: A Prospective Cohort Study

BACKGROUND

Mass drug administration (MDA) may further reduce malaria transmission in low-transmission areas. The impact of MDA on the dynamics of malaria transmission was determined in a prospective cohort study.

METHODS

Annual rounds of MDA with dihydroartemisinin-piperaquine (DP) were implemented were implemented in 2014 and 2015 in six village pairs before the malaria transmission season. Blood samples were collected from residents between July and December for microscopy and nested PCR. Incidence and prevalence of infection, clinical disease, and risk of malaria reinfection post-MDA were determined.

RESULTS

Coverage of three DP doses was 68.2% (2014) and 65.6% (2015), compliance was greater than 80%. Incidence of infection was significantly lower in 2014 (incidence rate [IR] = 0.2 per person year [PPY]) than in 2013 (IR = 1.1 PPY; P < .01); monthly infection prevalence declined in the first three months post-MDA. Clinical malaria incidence was lower in 2014 (IR = 0.1 PPY) and 2015 (IR = 0.2 PPY) than in 2013 (IR = 0.4 PPY; P < .01), but remained higher in eastern Gambia. Individuals infected before MDA had a 2-fold higher odds of reinfection post-MDA (adjusted odds ratio = 2.5, 95% confidence interval 1.5-4.3; P < .01).

CONCLUSIONS

MDA reduced malaria infection and clinical disease during the first months. The reduction was maintained in low-transmission areas, but not in eastern Gambia. Annual MDA could be followed by focal MDA targeting individuals infected during the dry season. Repeated MDA rounds, some during the dry season over larger geographical areas, may result in a more marked and sustained decrease of malaria transmission.

Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa

Local and cross-border importation remain major challenges to malaria elimination and are difficult to measure using traditional surveillance data. To address this challenge, we systematically collected parasite genetic data and travel history from thousands of malaria cases across northeastern Namibia and estimated human mobility from mobile phone data. We observed strong fine-scale spatial structure in local parasite populations, providing positive evidence that the majority of cases were due to local transmission. This result was largely consistent with estimates from mobile phone and travel history data. However, genetic data identified more detailed and extensive evidence of parasite connectivity over hundreds of kilometers than the other data, within Namibia and across the Angolan and Zambian borders. Our results provide a framework for incorporating genetic data into malaria surveillance and provide evidence that both strengthening of local interventions and regional coordination are likely necessary to eliminate malaria in this region of Southern Africa.

Assessing Kwa-Zulu-Natal's progress towards malaria elimination and its readiness for sub-national verification

Background

The South African province of KwaZulu-Natal is rapidly approaching elimination status for malaria with a steady decline in local cases. With the possibility of achieving elimination in reach, the KZN malaria control programme conducted a critical evaluation of its practices and protocols to identify potential challenges and priorities to achieving elimination. Three fundamental questions were addressed: (1) How close is KZN to malaria elimination; (2) Are all systems required to pursue subnational verification of elimination in place; and (3) What priority interventions must be implemented to reduce local cases to zero?

Methods

Based on the 2017 World Health Organization Framework for Elimination, twenty-eight requirements were identified, from which forty-nine indicators to grade elimination progress were further stratified. Malaria data were extracted from the surveillance system and other programme data sources to calculate each indicator and semi-quantitatively rate performance into one of four categories to assess the provinces elimination preparedness.

Results

Across the key components a number of gaps were elucidated based on specific indicators. Out of the 49 indicators across these key components, 10 indicators (20%) were rated as fully implemented/well implemented, 11 indicators (22%) were rated as partially done/somewhat implemented/activity needs to be strengthened, and 12 indicators (24%) were rated as not done at all/not implemented/poor performance. Sixteen indicators (33%) could not be calculated due to lack of data or missing data.

Conclusions

The critical self-evaluation of programme performance has allowed the KZN malaria programme to plan to address key issues moving forward. Based on the findings from the checklist review process, planning exercises were conducted to improve lower-rating indicators, and a monitoring and evaluation framework was created to assess progress on a monthly basis. This is scheduled to be reviewed annually to ensure continued progress toward meeting the elimination goal. In addition, multiple dissemination meetings were held with both provincial senior management and operational staff to ensure ownership of the checklist and its action plan at all levels.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2739-5) contains supplementary material, which is available to authorized users.

Human population movement and behavioural patterns in malaria hotspots on the Thai-Myanmar border: implications for malaria elimination

BACKGROUND

Malaria is heterogeneously distributed across landscapes. Human population movement (HPM) could link sub-regions with varying levels of transmission, leading to the persistence of disease even in very low transmission settings. Malaria along the Thai-Myanmar border has been decreasing, but remains heterogeneous. This study aimed to measure HPM, associated predictors of travel, and HPM correlates of self-reported malaria among people living within malaria hotspots.

METHODS

526 individuals from 279 households in two malaria hotspot areas were included in a prospective observational study. A baseline cross-sectional study was conducted at the beginning, recording both individual- and household-level characteristics. Individual movement and travel patterns were repeatedly observed over one dry season month (March) and one wet season month (May). Descriptive statistics, random effects logistic regressions, and logistic regressions were used to describe and determine associations between HPM patterns, individual-, household-factors, and self-reported malaria.

RESULTS

Trips were more common in the dry season. Malaria risk was related to the number of days doing outdoor activities in the dry season, especially trips to Myanmar, to forest areas, and overnight trips. Trips to visit forest areas were more common among participants aged 20-39, males, individuals with low income, low education, and especially among individuals with forest-related occupations. Overnight trips were more common among males, and individual with forest-related occupations. Forty-five participants reported having confirmed malaria infection within the last year. The main place of malaria blood examination and treatment was malaria post and malaria clinic, with participants usually waiting for 2-3 days from onset fever to seeking diagnosis. Individuals using bed nets, living in houses with elevated floors, and houses that received indoor residual spraying in the last year were less likely to report malaria infection.

CONCLUSION

An understanding of HPM and concurrent malaria dynamics is important for consideration of targeted public health interventions. Furthermore, diagnosis and treatment centres must be capable of quickly diagnosing and treating infections regardless of HPM. Coverage of diagnosis and treatment centres should be broad, maintained in areas bordering malaria hotspots, and available to all febrile individuals.

Predicting the direct and indirect impacts of climate change on malaria in coastal Kenya

Background

The transmission of malaria is highly variable and depends on a range of climatic and anthropogenic factors. This study investigates the combined, i.e. direct and indirect, impacts of climate change on the dynamics of malaria through modifications in: (i) the sporogonic cycle of Plasmodium induced by air temperature increase, and (ii) the life cycle of Anopheles vector triggered by changes in natural breeding habitat arising from the altered moisture dynamics resulting from acclimation responses of vegetation under climate change. The study is performed for a rural region in Kilifi county, Kenya.

Methods and findings

We use a stochastic lattice-based malaria (SLIM) model to make predictions of changes in Anopheles vector abundance, the life cycle of Plasmodium parasites, and thus malaria transmission under projected climate change in the study region. SLIM incorporates a nonlinear temperature-dependence of malaria parasite development to estimate the extrinsic incubation period of Plasmodium. It is also linked with a spatially distributed eco-hydrologic modeling framework to capture the impacts of climate change on soil moisture dynamics, which served as a key determinant for the formation and persistence of mosquito larval habitats on the land surface. Malaria incidence data collected from 2008 to 2013 is used for SLIM model validation. Projections of climate change and human population for the region are used to run the models for prediction scenarios.

Under elevated atmospheric CO₂ concentration ([CO₂]) only, modeled results reveal wetter soil moisture in the root zone due to the suppression of transpiration from vegetation acclimation, which increases the abundance of Anopheles vectors and the risk of malaria. When air temperature increases are also considered along with elevated [CO₂], the life cycle of Anopheles vector and the extrinsic incubation period of Plasmodium parasites are shortened nonlinearly. However, the reduction of soil moisture resulting from higher evapotranspiration due to air temperature increase also reduces the larval habitats of the vector. Our findings show the complicated role of vegetation acclimation under elevated [CO₂] on malaria dynamics and indicate an indirect but ignored impact of air temperature increase on malaria transmission through reduction in larval habitats and vector density.

Conclusions

Vegetation acclimation triggered by elevated [CO₂] under climate change increases the risk of malaria. In addition, air temperature increase under climate change has opposing effects on mosquito larval habitats and the life cycles of both Anopheles vectors and Plasmodium parasites. The indirect impacts of temperature change on soil moisture dynamics are significant and should be weighed together with the direct effects of temperature change on the life cycles of mosquitoes and parasites for future malaria prediction and control.

Use of open mobile mapping tool to assess human mobility traceability in rural offline populations with contrasting malaria dynamics

Infectious disease dynamics are affected by human mobility more powerfully than previously thought, and thus reliable traceability data are essential. In rural riverine settings, lack of infrastructure and dense tree coverage deter the implementation of cutting-edge technology to collect human mobility data. To overcome this challenge, this study proposed the use of a novel open mobile mapping tool, GeoODK. This study consists of a purposive sampling of 33 participants in six villages with contrasting patterns of malaria transmission that demonstrates a feasible approach to map human mobility. The self-reported traceability data allowed the construction of the first human mobility framework in rural riverine villages in the Peruvian Amazon. The mobility spectrum in these areas resulted in travel profiles ranging from 2 hours to 19 days; and distances between 10 to 167 km. Most Importantly, occupational-related mobility profiles with the highest displacements (in terms of time and distance) were observed in commercial, logging, and hunting activities. These data are consistent with malaria transmission studies in the area that show villages in watersheds with higher human movement are concurrently those with greater malaria risk. The approach we describe represents a potential tool to gather critical information that can facilitate malaria control activities.

Estimating sources and sinks of malaria parasites in Madagascar

In areas where malaria epidemiology is spatially and temporally heterogeneous, human-mediated parasite importation can result in non-locally acquired clinical cases and outbreaks in low-transmission areas. Using mobility estimates derived from the mobile phone data and spatial malaria prevalence data, we identify travel routes relevant to malaria transmission in Madagascar. We find that the primary hubs of parasite importation are in a spatially connected area of the central highlands. Surprisingly, sources of these imported infections are not spatially clustered. We then related these source locations directly to clinical cases in the low-transmission area of the capital. We find that in the capital, a major sink, the primary sources of infection are along the more populated coastal areas, although these sources are seasonally variable. Our results have implications for targeting interventions at source locations to achieve local or national malaria control goals.

Using Google Location History data to quantify fine-scale human mobility

Background

Human mobility is fundamental to understanding global issues in the health and social sciences such as disease spread and displacements from disasters and conflicts. Detailed mobility data across spatial and temporal scales are difficult to collect, however, with movements varying from short, repeated movements to work or school, to rare migratory movements across national borders. While typical sources of mobility data such as travel history surveys and GPS tracker data can inform different typologies of movement, almost no source of readily obtainable data can address all types of movement at once.

Methods

Here, we collect Google Location History (GLH) data and examine it as a novel source of information that could link fine scale mobility with rare, long distance and international trips, as it uniquely spans large temporal scales with high spatial granularity. These data are passively collected by Android smartphones, which reach increasingly broad audiences, becoming the most common operating system for accessing the Internet worldwide in 2017. We validate GLH data against GPS tracker data collected from Android users in the United Kingdom to assess the feasibility of using GLH data to inform human movement.

Results

We find that GLH data span very long temporal periods (over a year on average in our sample), are spatially equivalent to GPS tracker data within 100 m, and capture more international movement than survey data. We also find GLH data avoid compliance concerns seen with GPS trackers and bias in self-reported travel, as GLH is passively collected. We discuss some settings where GLH data could provide novel insights, including infrastructure planning, infectious disease control, and response to catastrophic events, and discuss advantages and disadvantages of using GLH data to inform human mobility patterns.

Conclusions

GLH data are a greatly underutilized and novel dataset for understanding human movement. While biases exist in populations with GLH data, Android phones are becoming the first and only device purchased to access the Internet and various web services in many middle and lower income settings, making these data increasingly appropriate for a wide range of scientific questions.

Electronic supplementary material

The online version of this article (10.1186/s12942-018-0150-z) contains supplementary material, which is available to authorized users.

Mathematical models of human mobility of relevance to malaria transmission in Africa

As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3–5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of their ability to predict the observed movement patterns – a gravity model, in which movement rates between pairs of locations increase with population size and decrease with distance, and a radiation model, in which travelers are cumulatively “absorbed” as they move outwards from their origin of travel. The gravity model provided a better fit to the data overall and for travel to large populations, while the radiation model provided a better fit for nearby populations. One strength of the data set was that trips could be categorized according to traveler group – namely, women traveling with children in all survey countries and youth workers in Mali. For gravity models fitted to data specific to these groups, youth workers were found to have a higher travel frequency to large population centers, and women traveling with children a lower frequency. These models may help predict the spatial transmission of malaria parasites and inform strategies to control their spread.

Acceptability of a herd immunity-focused, transmission-blocking malaria vaccine in malaria-endemic communities in the Peruvian Amazon: an exploratory study

BACKGROUND

A transmission-blocking vaccine (TBV) to prevent malaria-infected humans from infecting mosquitoes has been increasingly considered as a tool for malaria control and elimination. This study tested the hypothesis that a malaria TBV would be acceptable among residents of a malaria-hypoendemic region.

METHODS

The study was carried out in six Spanish-speaking rural villages in the Department of Loreto in the Peruvian Amazon. These villages comprise a cohort of 430 households associated with the Peru-Brazil International Centre for Excellence in Malaria Research. Individuals from one-third (143) of enrolled households in an ongoing longitudinal, prospective cohort study in 6 communities in Loreto, Peru, were randomly selected to participate by answering a pre-validated questionnaire.

RESULTS

All 143 participants expressed desire for a malaria vaccine in general; only 1 (0.7%) expressed unwillingness to receive a transmission-blocking malaria vaccine. Injection was considered most acceptable for adults (97.2%); for children drops in the mouth were preferred (96.8%). Acceptability waned marginally with the prospect of multiple injections (83.8%) and different projected efficacies at 70 and 50% (90.1 and 71.8%, respectively). Respondents demonstrated clear understanding that the vaccine was for community, rather than personal, protection against malaria infection.

DISCUSSION

In this setting of the Peruvian Amazon, a transmission-blocking malaria vaccine was found to be almost universally acceptable. This study is the first to report that residents of a malaria-endemic region have been queried regarding a malaria vaccine strategy that policy-makers in the industrialized world often dismiss as altruistic.

Low uptake of preventive interventions among malaria cases in Swaziland: towards malaria elimination

Settings: Swaziland is striving to achieve sustainable malaria elimination. Three preventive interventions are vital for reaching this goal: 1) effective household utilisation of long-lasting insecticide nets (LLINs), 2) indoor residual spraying (IRS), and 3) provision of chemoprophylaxis for those travelling to malaria-endemic areas. Objectives: To assess the uptake of preventive intervention among confirmed malaria cases. Design: A longitudinal study using nation-wide programme data from 2010 to 2015. Data on malaria cases from health facilities were sourced from the Malaria Surveillance Database System. Results: Of a total 2568 confirmed malaria cases in Swaziland, 2034 (79%) had complete data on case investigations and were included in the analysis. Of 341 (17%) individuals who owned LLINs, 169 (8%) used them; 338 (17%) had IRS and 314 (15%) slept in sprayed structures. Of 1403 travellers to areas at high malaria risk, 59 (4%) used any form of malaria prevention, including chemoprophylaxis. Conclusion: The uptake of all three key malaria prevention interventions is low, and could threaten the progress made thus far toward malaria elimination. Efforts to improve this situation, including qualitative research to understand the reasons for low uptake, are urgently needed.