Large-scale drivers of malaria and priority areas for prevention and control in the Brazilian Amazon region using a novel multi-pathogen geospatial model

Estimation and interpretation problems and solutions when using proportion covariates in linear regression models

Proportion variables, also known as compositional data, are very common in ecology. Unfortunately, few scientists are aware of how compositional data, when used as covariates, can adversely impact statistical analysis. We describe here how proportion covariates result in multicollinearity and parameter identifiability problems. Using simulated data on bird species richness as a function of land use, we show how these problems manifest when fitting a wide range of models in R, both in a frequentist and Bayesian framework. In particular, we show that similar models can often generate substantially different parameter estimates, leading to very different conclusions. Dropping a covariate or the intercept from the model can solve the multicollinearity and parameter identifiability problems. Unfortunately, these solutions do not fix the inherent challenges associated with interpreting parameter estimates. To this end, we propose focusing the interpretation on the difference of slope parameters to avoid the inherent unidentifiability of individual parameters. We also propose conditional plots with two x-axes and marginal plots as visualization techniques that can help users better interpret their modeling results. We illustrate these problems and proposed solutions using empirical data from the North American Breeding Bird Survey. The practical and straightforward approaches suggested in this article will help the fitting of linear models and interpretation of its results when some of the covariates are proportions.

Environmental and socio-economic determinants of the occurrence of malaria clusters in Colombia

This study identifies the environmental and socio-economic determinants of clusters of high malaria incidence in Colombia during the period of 2008-2019. The malaria cases were obtained from the National System of Surveillance in Public Health, with 798,897 cases reported in the 986 Colombian municipalities evaluated during the study period. Spatial autocorrelation of incidence was examined with global and local indices. Clusters were identified in the Amazon, Pacific, and Uraba-Bajo Cauca-Alto Sinú regions. The factors associated with a municipality belonging to a high-incidence cluster were identified using a logistic regression model with mixed effects and showed a positive association for the variables (forest coverage and minimum multi-year average rainfall). An inverse relationship was observed for aqueduct coverage and the odds of belonging to a cluster. A 1% increase in forest coverage was associated with a 4.2% increase in the odds of belonging to a malaria cluster. The association with minimum multi-year average rainfall was positive (OR = 1.0011; 95% CI 1.0005-1.0027). A 1% increase in aqueduct coverage was associated with a 4.3% decrease in the odds of belonging to malaria cluster. The identification of malaria cluster determinants in Colombia could help guide surveillance and disease control policies.

Cross-border malaria in the triple border region between Brazil, Venezuela and Guyana

The state of Roraima, in Brazil, has recently seen an increase in the number of reported Plasmodium falciparum infections believed to be imported from neighboring countries. The objective of this study was to determine the prevalence of Plasmodium species among patients attending malaria health posts in Roraima and quantify the infections attributable to imported malaria. This cross-sectional case study was carried out between March 2016 and September 2018. Study participants were recruited as they exited the malaria health post. Information about residence, occupation and travel history was collected using a questionnaire. A dried blood spot was collected and used for malaria diagnosis by PCR. A total of 1222 patients were enrolled. Of the 80% Plasmodium positive samples, 50% were P. falciparum, 34% P. vivax, 8% mixed P. falciparum/P. vivax and 0.2% mixed P. falciparum/P. ovale infections and 8% tested positive for Plasmodium, but the species could not be identified. 80% of the malaria patients likely acquired infections in Venezuela and the remaining 20% acquired in Guyana, Brazil, Suriname and French Guyana. 50% of the study participants reported to be working in a mine. Results from this study support the hypothesis that imported malaria contribute to the bulk of malaria diagnosed in Roraima. These findings are in keeping with previous findings and should be considered when developing malaria control interventions.

Human-centered design process and solutions to promote malaria testing and treatment seeking behavior in Guyana hinterlands

Background

Malaria is a persistent public health challenge among miners and other hard-to-reach populations in Guyana’s hinterland, specifically in Regions 1, 7, 8, and 9. Despite an overall decrease in malaria prevalence throughout Guyana, it remains common among mining populations whose work conditions both contribute toward malaria transmission and make it difficult to seek timely, Ministry of Health (MoH) approved malaria testing and treatment services. In an effort to develop innovative approaches to address this public health challenge, an interdisciplinary team of public health professionals, designers, and mining organizations collaborated using a human-centered design (HCD) process facilitated by the USAID-funded Breakthrough ACTION Guyana project in partnership with the MoH.

Methods

This paper describes two phases: [1] Define and [2] Design & Test. In the Define phase, following a literature review, we conducted 108 qualitative interviews with miners, camp managers, trained malaria testers, health workers, and other key stakeholders to understand experiences and challenges when seeking malaria testing and treatment services. These interviews were synthesized into 11 insights on issues such as risk perception, malaria knowledge, preventive behaviors, traditional and self-treatment, adherence to the correct treatment, testing, and coordination and communication gaps. From these insights, during the Design & Test phase, we developed 33 “How might we…?” questions which led to 792 ideas, of which eight emergent concepts were prototyped and refined in the field with 145 miners, camp managers, and stakeholders.

Results

The five final prototypes included: “Little Mosquito, Big Problem” social behavior change campaign; rapid counseling cards; branded malaria testing and treatment services; innovations in treatment adherence; and a participants, content, and logistics approach.

Conclusion

When applying HCD to public health issues, there are both opportunities and challenges to reconcile gaps that may exist between the two disciplines. However, HCD provides additional tools and mindsets to generatively work with migrant and mobile mining communities to encourage malaria testing and treatment services.

Burden of malaria in children under five and caregivers' health-seeking behaviour for malaria-related symptoms in artisanal mining communities in Ghana

Background

Artisanal mining creates enabling breeding ground for the vector of malaria parasites. There is paucity of data on the effects of artisanal mining on malaria. This study assessed burden of malaria and caregivers’ health-seeking behaviour for children under five in artisanal mining communities in East Akim District in Ghana.

Methods

A cross-sectional study involving caregivers and their children under five was conducted in three artisanal mining communities in the East Akim District in Ghana. Caregivers were interviewed using a structured questionnaire. Finger prick blood samples were collected and analysed for haemoglobin concentration using a rapid diagnostic test, and thick and thin blood smears were analysed to confirm the presence of malaria parasites.

Results

Of the 372 children under 5 years included in the study, 197 (53.1%) were male, with a mean age (± SD) of 23.0 ± 12.7 months. The proportion of children with malaria (Plasmodium falciparum and P. malariae) was 98.1% and 1.9%, respectively, whilst the proportion with anaemia (Hb < 11.0 g/dl) was 39.5% (n = 147). Almost all caregivers were female (98.9%), and 28.6% (n = 106) did not have access to any malaria control information. Caregivers associated malaria infection with mosquito bites (68.3%, n = 254) and poor sanitation (21.2%, n = 79). Malaria in children under five was significantly associated with anaemia (OR 11.07, 95% CI 6.59–18.68, n = 111/160, 69.4%; P < 0.0001), residing close to stagnant water (≤ 25 m) from an artisanal mining site (AOR 2.91, 95% CI 1.47–5.76, P = 0.002) and caregiver age younger than 30 years (OR 0.44, 95% CI 0.208–0.917, n = 162, 43.55%, P = 0.001).

Conclusions

There is a high burden of malaria and anaemia among children under five in artisanal mining communities of the East Akim District, and far higher than in non-artisanal mining sites. Interventions are needed to effectively regulate mining activities in these communities, and strengthen malaria control and health education campaigns to curtail the high malaria burden and improve health-seeking behaviour.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-04919-8.

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.

Impact of 1.5 oC and 2 oC global warming scenarios on malaria transmission in East Africa

Background: Malaria remains a global challenge with approximately 228 million cases and 405,000 malaria-related deaths reported in 2018 alone; 93% of which were in sub-Saharan Africa. Aware of the critical role than environmental factors play in malaria transmission, this study aimed at assessing the relationship between precipitation, temperature, and clinical malaria cases in East Africa and how the relationship may change under 1.5 ^oC and 2.0 ^oC global warming levels (hereinafter GWL1.5 and GWL2.0, respectively).

Methods: A correlation analysis was done to establish the current relationship between annual precipitation, mean temperature, and clinical malaria cases. Differences between annual precipitation and mean temperature value projections for periods 2008-2037 and 2023-2052 (corresponding to GWL1.5 and GWL2.0, respectively), relative to the control period (1977-2005), were computed to determine how malaria transmission may change under the two global warming scenarios.

Results: A predominantly positive/negative correlation between clinical malaria cases and temperature/precipitation was observed. Relative to the control period, no major significant changes in precipitation were shown in both warming scenarios. However, an increase in temperature of between 0.5 ^oC and 1.5 ^oC and 1.0 ^oC to 2.0 ^oC under GWL1.5 and GWL2.0, respectively, was recorded. Hence, more areas in East Africa are likely to be exposed to temperature thresholds favourable for increased malaria vector abundance and, hence, potentially intensify malaria transmission in the region.

Conclusions: GWL1.5 and GWL2.0 scenarios are likely to intensify malaria transmission in East Africa. Ongoing interventions should, therefore, be intensified to sustain the gains made towards malaria elimination in East Africa in a warming climate.

Impact of 1.5 oC and 2 oC global warming scenarios on malaria transmission in East Africa

Background: Malaria remains a global challenge with approximately 228 million cases and 405,000 malaria-related deaths reported in 2018 alone; 93% of which were in sub-Saharan Africa. Aware of the critical role than environmental factors play in malaria transmission, this study aimed at assessing the relationship between precipitation, temperature, and clinical malaria cases in East Africa and how the relationship may change under 1.5 oC and 2.0 oC global warming levels (hereinafter GWL1.5 and GWL2.0, respectively). Methods: A correlation analysis was done to establish the current relationship between annual precipitation, mean temperature, and clinical malaria cases. Differences between annual precipitation and mean temperature value projections for periods 2008-2037 and 2023-2052 (corresponding to GWL1.5 and GWL2.0, respectively), relative to the control period (1977-2005), were computed to determine how malaria transmission may change under the two global warming scenarios. Results: A predominantly positive/negative correlation between clinical malaria cases and temperature/precipitation was observed. Relative to the control period, no major significant changes in precipitation were shown in both warming scenarios. However, an increase in temperature of between 0.5 oC and 1.5 oC and 1.0 oC to 2.0 oC under GWL1.5 and GWL2.0, respectively, was recorded. Hence, more areas in East Africa are likely to be exposed to temperature thresholds favourable for increased malaria vector abundance and, hence, potentially intensify malaria transmission in the region. Conclusions: GWL1.5 and GWL2.0 scenarios are likely to intensify malaria transmission in East Africa. Ongoing interventions should, therefore, be intensified to sustain the gains made towards malaria elimination in East Africa in a warming climate.

The top 1%: quantifying the unequal distribution of malaria in Brazil

Background

As malaria endemic countries strive towards elimination, intensified spatial heterogeneities of local transmission could undermine the effectiveness of traditional intervention policy.

Methods

The dynamic nature of large-scale and long-term malaria heterogeneity across Brazilian Amazon basin were explored by (1) exploratory analysis of Brazil’s rich clinical malaria reporting database from 2004 to 2018, and (2) adapting Gini coefficient to study the distribution of malaria cases in the region.

Results

As transmission declined, heterogeneity increased with cases clustering into smaller subpopulations across the territory. In 2004, the 1% of health units with the greatest number of cases accounted for 46% of all reported Plasmodium vivax cases, whereas in 2018 52% of P. vivax cases occurred in the top 1% of health units. Plasmodium falciparum had lower levels of transmission than P. vivax, and also had greater levels of heterogeneity with 75% of cases occurring in the top 1% of health units. Age and gender stratification of cases revealed peri-domestic and occupational exposure settings that remained relatively stable.

Conclusion

The pathway to decreasing incidence is characterized by higher proportions of cases in males, in adults, due to importation, and caused by P. vivax. Characterization of spatio-temporal heterogeneity and risk groups can aid stratification for improved malaria control towards elimination with increased heterogeneity potentially allowing for more efficient and cost-effective targeting. Although distinct epidemiological phenomena were clearly observed as malaria transmission declines, the authors argue that there is no canonical path to malaria elimination and a more targeted and dynamic surveillance will be needed if Brazil decides to adopt the elimination target.

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

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

Long-lasting infectivity of Plasmodium vivax present in malarial patient blood to Anopheles aquasalis

Experimental studies for understanding the relationship between Plasmodium vivax and its vector hosts are difficult, because of to the lack of a long-term, in vitro continuous culture system unavailability of infected blood samples, seasonality of the disease, and the concentration of most cases in remote areas. This study evaluates the duration of the infectivity of P. vivax to Anopheles aquasalis after collecting blood from malaria-infected patients. Blood was collected from patients and stored at 4 °C and 37 °C. Every day, for 4 days, the blood was fed to An. aquasalis adult females, and a Giemsa-stained thick blood smear was mounted to account for sexual (gametocytes) and asexual (trophozoites and schizonts) stages and calculate parasitemia. Oocysts in the midgut of the mosquitoes were counted on the seventh day after feeding. Kruskal-Wallis test was used to compare the mean number of oocysts (MO) and the parasite density (PD) in each storage condition and post-infection time-points. The Mann-Whitney test was used to compare the number of oocysts for each day between temperatures. The results show that P. vivax stored at 4 °C and at 37 °C has its infectivity to An. aquasalis preserved for 2 days and 3 days, respectively. Infection rate (IR), PD and MO were higher on the day of blood collection and decreased gradually over time. The parasite density (number of parasites/μL) diminished faster at 4 °C than at 37 °C. In this study, a preservation protocol is shown for long-lasting infectivity of P. vivax in a blood sample taken from malaria-infected patients. These results show that infectivity of P. vivax stored at 4 °C and at 37 °C to An. aquasalis persist until 3 days after blood collection, but parasite density, infection rate, and mean of oocysts decreased 24h after blood collection. Since the malaria cases are increasingly far from the urban areas these results indicate that is possible, losing some infectivity, to realize experimental infections several dozen hours after the blood collection. However, it is necessary to improve the procedures for preserving P. vivax gametocytes for mosquito infection in the laboratory.

Malaria prevention and care seeking among gold miners in Guyana

Despite being a priority population in malaria elimination, there is scant literature on malaria-related behavior among gold miners. This study explores the prevalence and factors influencing malaria prevention, care seeking and treatment behaviors in Guyana gold mining camps. A cross sectional survey was conducted among adult gold miners living in mining camps in the hinterland Regions 1 (Barima-Waini), 7 (Cuyuni-Mazaruni), and 8 (Potaro-Siparuni). Multivariable logistic regressions explored factors associated with miners’ self-report of mosquito net use, prompt care-seeking; self-medication; and testing for malaria. A third of miners used a mosquito net the night preceding the survey and net use was higher among those who believed that net use was the norm in their camp (aOR: 3.11; 95% CI:1.65, 5.88). Less than half (45%) of miners had a fever in the past 12 months, among whom 36% sought care promptly, 48% tested positive for malaria while 54% self-medicated before seeking care. Prompt care-seeking was higher among miners with high malaria knowledge (aOR: 1.44; 95% CI: 1.01, 2.05). Similarly, testing rates increased with secondary education (aOR: 1.71; 95% CI: (1.16, 2.51), high malaria knowledge (aOR: 1.45; 95% CI: 1.02, 2.05), positive beliefs regarding malaria transmission, threat, self-diagnosis, testing and treatment, and, trust in government services (aOR: 1.59; 95% CI (1.12, 2.27) and experience of a prior malaria episode (aOR: 2.62; 95% CI: 1.71, 4.00). Self-medication was lower among male miners (aOR: 0. 52; 95% CI: 0.32, 0.86). Malaria prevention and care seeking behaviors among miners are somewhat low and influenced by mosquito net usage, perceived norms, malaria knowledge and prior episode of confirmed malaria. Study findings have implications for malaria interventions in the hinterland regions of Guyana such as the mass and continuous distribution of insecticide treated nets as well as community case management initiatives using trained malaria testing and treatment volunteers to curb malaria transmission among remote gold mining populations. These include efforts to identify and address gaps in distributing mosquito nets to miners and address miners’ barriers to prompt care seeking, malaria testing and treatment adherence. Targeted social and behavior change messaging is needed on net acquisition, use and care, prompt care-seeking, malaria testing and treatment adherence. Additional efforts to ensure the overall sustainability of the community case management initiative include increased publicity of the community case management initiative among miners, use of incentives to promote retention rates among the community case management volunteer testers and public private partnerships between the Guyana Ministry of Health and relevant mining organizations.

Mapping malaria seasonality in Madagascar using health facility data

BACKGROUND

Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. Identifying location-specific seasonality characteristics is useful for planning interventions. While most existing maps of malaria seasonality use fixed thresholds of rainfall, temperature, and/or vegetation indices to identify suitable transmission months, we construct a statistical modelling framework for characterising the seasonal patterns derived directly from monthly health facility data.

METHODS

With data from 2669 of the 3247 health facilities in Madagascar, a spatiotemporal regression model was used to estimate seasonal patterns across the island. In the absence of catchment population estimates or the ability to aggregate to the district level, this focused on the monthly proportions of total annual cases by health facility level. The model was informed by dynamic environmental covariates known to directly influence seasonal malaria trends. To identify operationally relevant characteristics such as the transmission start months and associated uncertainty measures, an algorithm was developed and applied to model realisations. A seasonality index was used to incorporate burden information from household prevalence surveys and summarise 'how seasonal' locations are relative to their surroundings.

RESULTS

Positive associations were detected between monthly case proportions and temporally lagged covariates of rainfall and temperature suitability. Consistent with the existing literature, model estimates indicate that while most parts of Madagascar experience peaks in malaria transmission near March-April, the eastern coast experiences an earlier peak around February. Transmission was estimated to start in southeast districts before southwest districts, suggesting that indoor residual spraying should be completed in the same order. In regions where the data suggested conflicting seasonal signals or two transmission seasons, estimates of seasonal features had larger deviations and therefore less certainty.

CONCLUSIONS

Monthly health facility data can be used to establish seasonal patterns in malaria burden and augment the information provided by household prevalence surveys. The proposed modelling framework allows for evidence-based and cohesive inferences on location-specific seasonal characteristics. As health surveillance systems continue to improve, it is hoped that more of such data will be available to improve our understanding and planning of intervention strategies.

A genetic algorithm for identifying spatially-varying environmental drivers in a malaria time series model

Time series models of malaria cases can be applied to forecast epidemics and support proactive interventions. Mosquito life history and parasite development are sensitive to environmental factors such as temperature and precipitation, and these variables are often used as predictors in malaria models. However, malaria-environment relationships can vary with ecological and social context. We used a genetic algorithm to optimize a spatiotemporal malaria model by aggregating locations into clusters with similar environmental sensitivities. We tested the algorithm in the Amhara Region of Ethiopia using seven years of weekly Plasmodium falciparum data from 47 districts and remotely-sensed land surface temperature, precipitation, and spectral indices as predictors. The best model identified six clusters, and the districts in each cluster had distinctive responses to the environmental predictors. We conclude that spatial stratification can improve the fit of environmentally-driven disease models, and genetic algorithms provide a practical and effective approach for identifying these clusters.

Disarmament is the New War, Gold is the New Opium, and Ecohealth is the Historic Victim

In Colombia, the convergence of drug trafficking, illegal armed groups, and gold production and trade threatens peace and stability in the post-FARC (Revolutionary Armed Forces of Colombia) era, as had the narcotics trade previously. Armed groups and criminal organizations have increased and consolidated their influence over illegal mining and may be diverting US$5 billion from Colombia's annual economy. As of 2014, 46% of the total area (78 939 ha) exploited for alluvial gold was in the Afro-Colombian Pacific States, in which unregulated mining was the main driver of deforestation. The informal job market represents 49% of the workforce and absent other economic alternatives, this workforce of ex-guerrillas, organized crime groups and corrupt officials will sustain the black markets that permeate gold mining. Human health consequences of unregulated gold mining are largely unrecognized, but include the spread of malaria and other insect-borne diseases, and we suggest diseases such as babesiosis.

Environmental and socioeconomic analysis of malaria transmission in the Brazilian Amazon, 2010-2015

OBJECTIVE

To analyze the environmental and socioeconomic risk factors of malaria transmission at municipality level, from 2010 to 2015, in the Brazilian Amazon.

METHODS

The municipalities were stratified into high, moderate, and low transmission based on the annual parasite incidence. A multinomial logistic regression that compared low with medium transmission and low with high transmission was performed. For each category, three models were analyzed: one only with socioeconomic risk factors (Gini index, illiteracy, number of mines and indigenous areas); a second with the environmental factors (forest coverage and length of the wet season); and a third with all covariates (full model).

RESULTS

The full model showed the best performance. The most important risks factors for high transmission were Gini index, length of the wet season and illiteracy, OR 2.06 (95%CI 1.19–3.56), 1.73 (95%CI 1.19–2.51) and 1.10 (95%CI 1.03–1.17), respectively. The medium transmission showed a weaker influence of the risk factors, being illiteracy, forest coverage and indigenous areas statistically significant but with marginal influence.

CONCLUSIONS

As a disease of poverty, the reduction in wealth inequalities and, therefore, health inequalities, could reduce the transmission considerably. Besides, environmental risk factors as length of the wet season should be considered in the planning, prevention and control. Municipality-level and fine-scale analysis should be done together to improve the knowledge of the local dynamics of transmission.

Spatial spread of malaria and economic frontier expansion in the Brazilian Amazon

The temporal and spatial evolution of malaria was described for the postfrontier phase of the Brazilian Amazon in 2003–2013. The current ecological study aimed to understand the relationship between spatial population mobility and the distribution of malaria cases. The study identified epidemiologically relevant areas using regional statistical modeling and spatial analyses that considered differential infections and types of work activities. Annual parasite incidence (API) in the region was highest in hotspots along the Amazon River and in the south and west settlement zone of Hiléia, with concentrations in environmental protection areas and açaí and Brazil nut extraction areas. The dispersal force decreased in the Central Amazon due to rapid urbanization and improved socioeconomic conditions for workers in consolidated settlement areas. The study characterized the spatial patterns of disease transmission according to the economic activity and regionalization of geographic areas, confirming that the incidence of infection by work activity and labor flow is linked to extractive activities and agricultural settlements.

Deforestation Increases the Risk of Scrub Typhus in Korea

Background: Scrub typhus is an important public health issue in Korea. Risk factors for scrub typhus include both individual-level factors and environmental drivers, and some are related to the increased density of vector mites and rodents, the natural hosts of the mites. In this regard, deforestation is a potential risk factor, because the deforestation-induced secondary growth of scrub vegetation may increase the densities of mites and rodents. To examine this hypothesis, this study investigated the association between scrub typhus and deforestation. Methods: We acquired district-level data for 2006-2017, including the number of cases of scrub typhus reported annually, deforestation level, and other covariates. Deforestation was assessed using preprocessed remote-sensing satellite data. Bayesian regression models, including Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models, were examined, and spatial autocorrelation was considered in hierarchical models. A sensitivity analysis was conducted using different accumulation periods for the deforestation level to examine the robustness of the association. Results: The final models showed a significant association between deforestation and the incidence of scrub typhus (relative risk = 1.20, 95% credible interval = 1.15-1.24). The sensitivity analysis gave consistent results, and a potential long-term effect of deforestation for up to 5 years was shown. Conclusion: The results support the potential public health benefits of forest conservation by suppressing the risk of scrub typhus, implying the need for strong engagement of public health sectors in conservation issues from a One Health perspective.

Malaria intensity in Colombia by regions and populations

Determining the distribution of disease prevalence among heterogeneous populations at the national scale is fundamental for epidemiology and public health. Here, we use a combination of methods (spatial scan statistic, topological data analysis and epidemic profile) to study measurable differences in malaria intensity by regions and populations of Colombia. This study explores three main questions: What are the regions of Colombia where malaria is epidemic? What are the regions and populations in Colombia where malaria is endemic? What associations exist between epidemic outbreaks between regions in Colombia? Plasmodium falciparum is most prevalent in the Pacific Coast, some regions of the Amazon Basin, and some regions of the Magdalena Basin. Plasmodium vivax is the most prevalent parasite in Colombia, particularly in the Northern Amazon Basin, the Caribbean, and municipalities of Sucre, Antioquia and Cordoba. We find an acute peak of malarial infection at 25 years of age. Indigenous and Afrocolombian populations experience endemic malaria (with household transmission). We find that Plasmodium vivax decreased in the most important hotspots, often with moderate urbanization rate, and was re-introduced to locations with moderate but sustained deforestation. Infection by Plasmodium falciparum, on the other hand, steadily increased in incidence in locations where it was introduced in the 2009-2010 generalized epidemic. Our findings suggest that Colombia is entering an unstable transmission state, where rapid decreases in one location of the country are interconnected with rapid increases in other parts of the country.

Abundance of impacted forest patches less than 5 km2 is a key driver of the incidence of malaria in Amazonian Brazil

The precise role that deforestation for agricultural settlements and commercial forest products plays in promoting or inhibiting malaria incidence in Amazonian Brazil is controversial. Using publically available databases, we analyzed temporal malaria incidence (2009–2015) in municipalities of nine Amazonian states in relation to ecologically defined variables: (i) deforestation (rate of forest clearing over time); (ii) degraded forest (degree of human disturbance and openness of forest canopy for logging) and (iii) impacted forest (sum of deforested and degraded forest patches). We found that areas affected by one kilometer square of deforestation produced 27 new malaria cases (r² = 0.78; F1,10 = 35.81; P < 0.001). Unexpectedly, we found both a highly significant positive correlation between number of impacted forest patches less than 5 km² and malaria cases, and that these patch sizes accounted for greater than ~95% of all patches in the study area. There was a significantly negative correlation between extraction forestry economic indices and malaria cases. Our results emphasize not only that deforestation promotes malaria incidence, but also that it directly or indirectly results in a low Human Development Index, and favors environmental conditions that promote malaria vector proliferation.

Analyzing the Local Epidemiological Profile of Malaria Transmission in the Brazilian Amazon Between 2010 and 2015

Introduction:

Malaria still is a public health problem in the Americas. In 2015, Brazil accounted for 37% of all cases in the Americas, and of these cases, 99.5% were located in the Brazilian Amazon. Despite the mobilization of resources from the Brazilian National Plan for Malaria Control, too many municipalities have high transmission levels. The objective of this study is to evaluate the local epidemiological profile of malaria and its trend between 2010 and 2015 in the Brazilian Amazon. This study also aims to recognize the epidemiological differences in the local temporo-spatial dynamics of malaria.

Methods:

Malaria data were stratified by the annual parasite incidence (API) over the six-year period and by municipality. We used the method of seasonal decomposition by Loess smoothing to capture trend, seasonal and irregular components. A generalized linear model was applied to quantify trends, and the Kruskal-Wallis Rank Sum was applied to test for seasonality significance.

Results:

The malaria API declined by 61% from 2010 to 2015, and there was a 40% reduction of municipalities with high transmission (determined as an API higher than 50). In 2015, 9.4% of municipalities had high transmission and included 62.8% of the total cases. The time-series analyses showed different incidence patterns by region after 2012; several states have minimized the effect of the seasonality in their incidence rates, thus achieving low rates of incidence. There were 13 municipalities with sustained high transmission that have become the principal focus of malaria control; these municipalities contained 40% of the cases between 2013 and 2015.

Discussion:

Brazil has achieved advances, but more sustained efforts are necessary to contain malaria resurgence. The use of malaria stratification has been demonstrated as a relevant tool to plan malaria programs more efficiently, and spatiotemporal analysis corroborates the idea that implementing any intervention in malaria should be stratified by time to interpret tendencies and by space to understand the local dynamics of the disease.

Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing

The prevention and control of mosquito-borne diseases, such as malaria, are important health issues in tropical areas. Malaria transmission is a multi-scale process strongly controlled by environmental factors, and the use of remote-sensing data is suitable for the characterization of its spatial and temporal dynamics. Synthetic aperture radar (SAR) is well-adapted to tropical areas, since it is capable of imaging independent of light and weather conditions. In this study, we highlight the contribution of SAR sensors in the assessment of the relationship between vectors, malaria and the environment in the Amazon region. More specifically, we focus on the SAR-based characterization of potential breeding sites of mosquito larvae, such as man-made water collections and natural wetlands, providing guidelines for the use of SAR capabilities and techniques in order to optimize vector control and malaria surveillance. In light of these guidelines, we propose a framework for the production of spatialized indicators and malaria risk maps based on the combination of SAR, entomological and epidemiological data to support malaria risk prevention and control actions in the field.

Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence

Considerable interest in the relationship between biodiversity and disease has recently captured the attention of the research community, with important public policy implications. In particular, malaria in the Amazon region is often cited as an example of how forest conservation can improve public health outcomes. However, despite a growing body of literature and an increased understanding of the relationship between malaria and land use / land cover change (LULC) in Amazonia, contradictions have emerged. While some studies report that deforestation increases malaria risk, others claim the opposite. Assessing malaria risk requires examination of dynamic processes among three main components: (i) the environment (i.e. LULC and landscape transformations), (ii) vector biology (e.g. mosquito species distributions, vector activity and life cycle, plasmodium infection rates), and (iii) human populations (e.g. forest-related activity, host susceptibility, movement patterns). In this paper, we conduct a systematic literature review on malaria risk and deforestation in the Amazon focusing on these three components. We explore key features that are likely to generate these contrasting results using the reviewed articles and our own data from Brazil and Peru, and conclude with suggestions for productive avenues in future research.

This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

malERA: An updated research agenda for characterising the reservoir and measuring transmission in malaria elimination and eradication

This paper summarises key advances in defining the infectious reservoir for malaria and the measurement of transmission for research and programmatic use since the Malaria Eradication Research Agenda (malERA) publication in 2011. Rapid and effective progress towards elimination requires an improved understanding of the sources of transmission as well as those at risk of infection. Characterising the transmission reservoir in different settings will enable the most appropriate choice, delivery, and evaluation of interventions. Since 2011, progress has been made in a number of areas. The extent of submicroscopic and asymptomatic infections is better understood, as are the biological parameters governing transmission of sexual stage parasites. Limitations of existing transmission measures have been documented, and proof-of-concept has been established for new innovative serological and molecular methods to better characterise transmission. Finally, there now exists a concerted effort towards the use of ensemble datasets across the spectrum of metrics, from passive and active sources, to develop more accurate risk maps of transmission. These can be used to better target interventions and effectively monitor progress toward elimination. The success of interventions depends not only on the level of endemicity but also on how rapidly or recently an area has undergone changes in transmission. Improved understanding of the biology of mosquito-human and human-mosquito transmission is needed particularly in low-endemic settings, where heterogeneity of infection is pronounced and local vector ecology is variable. New and improved measures of transmission need to be operationally feasible for the malaria programmes. Outputs from these research priorities should allow the development of a set of approaches (applicable to both research and control programmes) that address the unique challenges of measuring and monitoring transmission in near-elimination settings and defining the absence of transmission.

Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis

BACKGROUND

In the process of geographical retraction of malaria, some important endemicity pockets remain. Here, we report results from a study developed to obtain detailed community data from an important malaria hotspot in Latin America (Alto Juruá, Acre, Brazil), to investigate the association of malaria with socioeconomic, demographic and living conditions.

METHODS

A household survey was conducted in 40 localities (n = 520) of Mâncio Lima and Rodrigues Alves municipalities, Acre state. Information on previous malaria, schooling, age, gender, income, occupation, household structure, habits and behaviors related to malaria exposure was collected. Multiple correspondence analysis (MCA) was applied to characterize similarities between households and identify gradients. The association of these gradients with malaria was assessed using regression.

RESULTS

The first three dimensions of MCA accounted for almost 50% of the variability between households. The first dimension defined an urban/rurality gradient, where urbanization was associated with the presence of roads, basic services as garbage collection, water treatment, power grid energy, and less contact with the forest. There is a significant association between this axis and the probability of malaria at the household level, OR = 1.92 (1.23-3.02). The second dimension described a gradient from rural settlements in agricultural areas to those in forested areas. Access via dirt road or river, access to electricity power-grid services and aquaculture were important variables. Malaria was at lower risk at the forested area, OR = 0.55 (1.23-1.12). The third axis detected intraurban differences and did not correlate with malaria.

CONCLUSIONS

Living conditions in the study area are strongly geographically structured. Although malaria is found throughout all the landscapes, household traits can explain part of the variation found in the odds of having malaria. It is expected these results stimulate further discussions on modelling approaches targeting a more systemic and multi-level view of malaria dynamics.

A social-ecological database to advance research on infrastructure development impacts in the Brazilian Amazon

Recognized as one of the world's most vital natural and cultural resources, the Amazon faces a wide variety of threats from natural resource and infrastructure development. Within this context, rigorous scientific study of the region's complex social-ecological system is critical to inform and direct decision-making toward more sustainable environmental and social outcomes. Given the Amazon's tightly linked social and ecological components and the scope of potential development impacts, effective study of this system requires an easily accessible resource that provides a broad and reliable data baseline. This paper brings together multiple datasets from diverse disciplines (including human health, socio-economics, environment, hydrology, and energy) to provide investigators with a variety of baseline data to explore the multiple long-term effects of infrastructure development in the Brazilian Amazon.

Deforestation and malaria incidence in the legal Amazon Region between 1996 and 2012

Abstract Malaria is a major public health problem, and Brazil is the largest contributor in America to the number of cases. In the country, the Amazon concentrates around 99.5% of the cases. This article aims to compare trends in deforestation rate and the parasite index of malaria in the Amazon region between 1996 and 2012. The annual crude rate of deforestation and the Annual Parasite Index (API) of malaria between 1996 and 2012 were estimated. The rate of deforestation has great variability among the states every year, and a similar situation is observed for malaria API over the studied period. There are important variations across the states within this period. The historical series of crude deforestation rate and malaria API have markedly similar trends; with a 1-2 years lag between them, suggesting that the occurrence of fluctuations in deforestation numbers impacts malaria numbers in a period immediately following. The mapping of deforested areas and the analysis of temporal series are therefore useful in the analysis of malaria.

Epidemiological and entomological studies of a malaria outbreak among French armed forces deployed at illegal gold mining sites reveal new aspects of the disease's transmission in French Guiana

BACKGROUND

In December 2010, a Plasmodium vivax malaria outbreak occurred among French forces involved in a mission to control illegal gold mining in French Guiana. The findings of epidemiological and entomological investigations conducted after this outbreak are presented here.

METHODS

Data related to malaria cases reported to the French armed forces epidemiological surveillance system were collected during the epidemic period from December 2010 to April 2011. A retrospective cohort study was conducted to identify presumed contamination sites. Anopheles mosquitoes were sampled at the identified sites using Mosquito Magnet and CDC light traps. Specimens were identified morphologically and confirmed using molecular methods (sequencing of ITS2 gene and/or barcoding). Anopheles infections with Plasmodium falciparum and P. vivax were tested by both enzyme-linked immunosorbent assay and real-time PCR.

RESULTS

Seventy-two P. vivax malaria cases were reported (three were mixed P. falciparum/P. vivax infections), leading to a global attack rate of 26.5% (72/272). Lack of compliance with vector control measures and doxycycline chemoprophylaxis was reported by patients. Two illegal gold mining sites located in remote areas in the primary forest were identified as places of contamination. In all, 595 Anopheles females were caught and 528 specimens were formally identified: 305 Anopheles darlingi, 145 Anopheles nuneztovari s.l., 63 Anopheles marajoara and 15 Anopheles triannulatus s.l. Three An. darlingi were infected by P. falciparum (infection rate: 1.1%) and four An. marajoara by P. vivax (infection rate: 6.4%).

DISCUSSION

The main drivers of the outbreak were the lack of adherence by military personnel to malaria prevention measures and the high level of malaria transmission at illegal gold mining sites. Anopheles marajoara was clearly implicated in malaria transmission for the first time in French Guiana. The high infection rates observed confirm that illegal gold mining sites must be considered as high level malaria transmission areas in the territory.

CONCLUSIONS

Illegal gold mining activities are challenging the control of malaria in French Guiana. Collaboration with neighbouring countries is necessary to take into account mobile populations such as gold miners. Malaria control strategies in the French armed forces must be adapted to P. vivax malaria and sylvatic Anopheles species.

Predictive Malaria Risk and Uncertainty Mapping in Nchelenge District, Zambia: Evidence of Widespread, Persistent Risk and Implications for Targeted Interventions

Malaria risk maps may be used to guide policy decisions on whether vector control interventions should be targeted and, if so, where. Active surveillance for malaria was conducted through household surveys in Nchelenge District, Zambia from April 2012 through December 2014. Households were enumerated based on satellite imagery and randomly selected for study enrollment. At each visit, participants were administered a questionnaire and a malaria rapid diagnostic test (RDT). Logistic regression models were used to construct spatial prediction risk maps and maps of risk uncertainty. A total of 461 households were visited, comprising 1,725 participants, of whom 48% were RDT positive. Several environmental features were associated with increased household malaria risk in a multivariable logistic regression model adjusting for seasonal variation. The model was validated using both internal and external evaluation measures to generate and assess root mean square error, as well as sensitivity and specificity for predicted risk. The final, validated model was used to predict and map malaria risk including a measure of risk uncertainty. Malaria risk in a high, perennial transmission setting is widespread but heterogeneous at a local scale, with seasonal variation. Targeting malaria control interventions may not be appropriate in this epidemiological setting.

Reduction in symptomatic malaria prevalence through proactive community treatment in rural Senegal

OBJECTIVES

We piloted a community-based proactive malaria case detection model in rural Senegal to evaluate whether this model can increase testing and treatment and reduce prevalence of symptomatic malaria in target communities.

METHODS

Home care providers conducted weekly sweeps of every household in their village throughout the transmission season to identify patients with symptoms of malaria, perform rapid diagnostic tests (RDT) on symptomatic patients and provide treatment for positive cases. The model was implemented in 15 villages from July to November 2013, the high transmission season. Fifteen comparison villages were chosen from those implementing Senegal's original, passive model of community case management of malaria. Three sweeps were conducted in the comparison villages to compare prevalence of symptomatic malaria using difference in differences analysis.

RESULTS

At baseline, prevalence of symptomatic malaria confirmed by RDT for all symptomatic individuals found during sweeps was similar in both sets of villages (P = 0.79). At end line, prevalence was 16 times higher in the comparison villages than in the intervention villages (P = 0.003). Adjusting for potential confounders, the intervention was associated with a 30-fold reduction in odds of symptomatic malaria in the intervention villages (AOR = 0.033; 95% CI: 0.017, 0.065). Treatment seeking also increased in the intervention villages, with 57% of consultations by home care providers conducted between sweeps through routine community case management.

CONCLUSIONS

This pilot study suggests that community-based proactive case detection reduces symptomatic malaria prevalence, likely through more timely case management and improved care seeking behaviour. A randomised controlled trial is needed to further evaluate the impact of this model.