Social and environmental determinants of malaria in space and time in Viet Nam

The 2023 report of the MJA-Lancet Countdown on health and climate change: sustainability needed in Australia's health care sector

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021 and 2022. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the sixth report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. Our results highlight the health and economic costs of inaction on health and climate change. A series of major flood events across the four eastern states of Australia in 2022 was the main contributor to insured losses from climate-related catastrophes of $7.168 billion - the highest amount on record. The floods also directly caused 23 deaths and resulted in the displacement of tens of thousands of people. High red meat and processed meat consumption and insufficient consumption of fruit and vegetables accounted for about half of the 87 166 diet-related deaths in Australia in 2021. Correction of this imbalance would both save lives and reduce the heavy carbon footprint associated with meat production. We find signs of progress on health and climate change. Importantly, the Australian Government released Australia's first National Health and Climate Strategy, and the Government of Western Australia is preparing a Health Sector Adaptation Plan. We also find increasing action on, and engagement with, health and climate change at a community level, with the number of electric vehicle sales almost doubling in 2022 compared with 2021, and with a 65% increase in coverage of health and climate change in the media in 2022 compared with 2021. Overall, the urgency of substantial enhancements in Australia's mitigation and adaptation responses to the enormous health and climate change challenge cannot be overstated. Australia's energy system, and its health care sector, currently emit an unreasonable and unjust proportion of greenhouse gases into the atmosphere. As the Lancet Countdown enters its second and most critical phase in the leadup to 2030, the depth and breadth of our assessment of health and climate change will be augmented to increasingly examine Australia in its regional context, and to better measure and track key issues in Australia such as mental health and Aboriginal and Torres Strait Islander health and wellbeing.

Climate change and human health in Vietnam: a systematic review and additional analyses on current impacts, future risk, and adaptation

This study aims to investigate climate change's impact on health and adaptation in Vietnam through a systematic review and additional analyses of heat exposure, heat vulnerability, awareness and engagement, and projected health costs. Out of 127 reviewed studies, findings indicated the wider spread of infectious diseases, and increased mortality and hospitalisation risks associated with extreme heat, droughts, and floods. However, there are few studies addressing health cost, awareness, engagement, adaptation, and policy. Additional analyses showed rising heatwave exposure across Vietnam and global above-average vulnerability to heat. By 2050, climate change is projected to cost up to USD1-3B in healthcare costs, USD3-20B in premature deaths, and USD6-23B in work loss. Despite increased media focus on climate and health, a gap between public and government publications highlighted the need for more governmental engagement. Vietnam's climate policies have faced implementation challenges, including top-down approaches, lack of cooperation, low adaptive capacity, and limited resources.

Serological evaluation of risk factors for exposure to malaria in a pre-elimination setting in Malaysian Borneo

Malaysia has reported no indigenous cases of P. falciparum and P. vivax for over 3 years. When transmission reaches such low levels, it is important to understand the individuals and locations where exposure risks are high, as they may be at greater risk in the case of a resurgence of transmission. Serology is a useful tool in low transmission settings, providing insight into exposure over longer durations than PCR or RDT. We ran blood samples from a 2015 population-based survey in northern Sabah, Malaysian Borneo on a multiplex bead assay. Using supervised machine learning methods, we characterised recent and historic exposure to Plasmodium falciparum and P. vivax and found recent exposure to P. falciparum to be very low, with exposure to both species increasing with age. We performed a risk-factor assessment on environmental, behavioural, demographic and household factors, and identified forest activity and longer travel times to healthcare as common risk-factors for exposure to P. falciparum and P. vivax. In addition, we used remote-sensing derived data and geostatistical models to assess environmental and spatial associations with exposure. We created predictive maps of exposure to recent P. falciparum in the study area and showed 3 clear foci of exposure. This study provides useful insight into the environmental, spatial and demographic risk factors for P. falciparum and P. vivax at a period of low transmission in Malaysian Borneo. The findings would be valuable in the case of resurgence of human malarias in the region.

The relationship between climate change and malaria in South-East Asia: A systematic review of the evidence

Background: Climatic change is an inescapable fact that implies alterations in seasons where weather occurrences have their schedules shift from the regular and magnitudes intensify to more extreme variations over a multi-year period. Southeast Asia is one of the many regions experiencing changes in climate and concurrently still has endemicities of malaria. Given that previous studies have suggested the influence of climate on malaria's vector the Anopheles mosquitoes and parasite the Plasmodium group, this study was conducted to review the evidence of associations made between malaria cases and climatic variables in Southeast Asia throughout a multi-year period. Methods: Our systematic literature review was informed by the PRISMA guidelines and registered in PROSPERO: CRD42022301826 on 5 th February 2022. We searched for original articles in English and Indonesian that focused on the associations between climatic variables and malaria cases. Results: The initial identification stage resulted in 535 records of possible relevance and after abstract screening and eligibility assessment we included 19 research articles for the systematic review. Based on the reviewed articles, changing temperatures, precipitation, humidity and windspeed were considered for statistical association across a multi-year period and are correlated with malaria cases in various regions throughout Southeast Asia. Conclusions: According to the review of evidence, climatic variables that exhibited a statistically significant correlation with malaria cases include temperatures, precipitation, and humidity. The strength of each climatic variable varies across studies. Our systematic review of the limited evidence indicates that further research for the Southeast Asia region remains to be explored.

Seasonal Distribution and Trend Analysis of Urban Malaria Prevalence in a Malaria Clinic, South Delhi, India, between 2012 and 2019

It is important to study the recent malaria incidence trends in urban areas resulting from rapid urbanization that can lead to changes in environmental conditions for malaria. This retrospective study assessed trends in malaria patients, their distribution according to parasite species, patient demographics, and weather data for the past 8 years at a malaria clinic in the National Institute of Malaria Research, New Delhi, India. We overlaid the effects of environmental factors such as rainfall, relative humidity, and temperature on malaria incidence. The malaria data were digitized for a period spanning 2012 to 2019, during which 36,892 patients with fever attended the clinic. Of these, 865 (2.3%) were diagnosed with malaria microscopically. Plasmodium vivax was predominant (96.2%), and very few patients were of Plasmodium falciparum (3.5%) or mixed infections (0.3%). The patients with malaria were within a 10-km radius of the clinic. Males (70.9%) were more commonly affected than females (29.1%). Of the total malaria patients, a majority (∼78%) belonged to the > 15-year age group. A total of 593 malaria patients (68.6%) received primaquine. These patients were most commonly diagnosed in April through October. Furthermore, there was a lag of 1 month between the rainfall peak and the malaria case peak. The peak in malaria cases corresponded to a mean temperature of 25 to 30°C and a relative humidity of 60% to 80%. This analysis will be useful for policymakers in evaluating current interventions and in accelerating malaria control further in urban areas of India.

A comparison of malaria prevention behaviours, care-seeking practices and barriers between malaria at-risk worksite migrant workers and villagers in Northern Shan State, Myanmar-a mixed method study

Background

Migrant populations are at an increased risk of exposure to malaria due to their nature of work and seasonal migration. This study aimed to compare malaria prevention behaviours and care-seeking practices among worksite migrant workers and villagers in the malaria-at-risk areas of Eastern Myanmar close to the China border.

Methods

A mixed method study was conducted in March 2019. The malaria-at-risk worksites in the four targeted townships, and villages located the nearest to these worksites were approached. Key stakeholders, such as worksite managers and village leaders, were interviewed.

Results

A total of 23 worksites, which employed 880 migrants and 447 locals, and 20 villages, which were homes for 621 migrants and 9731 locals, were successfully interviewed. Regarding malaria prevention behaviours, sleeping under a bed net was common among both worksites (74%) and villages (85%). In contrast, insecticide-treated nets/long-lasting insecticidal nets (ITN/LLIN) usage was much lower in the worksites than in the villages (39% vs 80%). Regarding care-seeking practices for febrile illness, self-medication was a popular choice for both worksite workers and villagers owing to the easy availability of western medicine. Moreover, local-belief-driven traditional practices were more common among villagers. For occasions in which fever was not relieved, both would seek health care from rural health centres, private clinics, or public hospitals. As for barriers, villagers mostly cited language barriers, which often lead to misunderstanding between health providers and them. In contrast, most of the worksites cited logistics issues as they were in remote areas with devastated road conditions and the routes to formal health facilities were not secure due to frequent armed conflicts.

Conclusion

This study demonstrated that site-workers and villagers had different malaria prevention behaviours and care-seeking practices even though they resided in the same geographic area. Hence, it is important to recognize such differences for more effective intervention approaches.

Aggregate-level Lead Exposure and Child Maltreatment

The purpose of this study was to examine the possible ecological association between aggregate blood lead levels (BLL) and rates of child maltreatment. To this end, we employed an ecologic study design, analyzing results from 59,645 child BLL tests between the years 1996 and 2007, and 6,640 substantiated maltreatment investigations from 2006 to 2016 in a large Midwest city. Separate Bayesian spatial Poisson conditional autoregressive (CAR) and Bayesian spatial zero-inflated Poisson CAR models were used to predict the occurrence of maltreatment.Bivariate results showed that aggregate rates of maltreatment increased as aggregate BLL increased. Multivariate results showed that medium-exposure BLL census tracts (OR = 1.38) and high-exposure BLL tracts (OR = 1.38) had increased odds of substantiated investigations for any maltreatment compared to low BLL census tracts even after controlling for crime rates, age of the housing stock, and concentrated disadvantage. Our findings, considered with prior research, continue to reveal a confluence of deleterious outcomes in areas where exposure to lead seems elevated. In this case, child maltreatment also appears to represent a macro-level correlate of aggregate lead exposure. Yet our results preclude any causal inference, and further research on the intersection of child maltreatment with environmental toxins is needed to determine if contaminant abatement should be considered as a possible maltreatment prevention strategy.

Modelling sociodemographic factors that affect malaria prevalence in Sussundenga, Mozambique: a cross-sectional study

Background: Malaria is still one of the leading causes of mortality and morbidity in Mozambique with little progress in malaria control over the past 20 years. Sussundenga is one of most affected areas. Malaria transmission has a strong association with environmental and sociodemographic factors. The knowledge of sociodemographic factors that affects malaria, may be used to improve the strategic planning for its control. Currently such studies have not been performed in Sussundenga. Thus, the objective of this study is to model the relationship between malaria and sociodemographic factors in Sussundenga, Mozambique.

Methods: Houses in the study area were digitalized and enumerated using Google Earth Pro version 7.3. In this study 100 houses were randomly selected to conduct a community survey of Plasmodiumfalciparum parasite prevalence using rapid diagnostic test (RDT). During the survey, a questionnaire was conducted to assess the sociodemographic factors of the participants. Descriptive statistics were analyzed and backward stepwise logistic regression was performed establishing a relationship between positive cases and the factors. The analysis was carried out using SPSS version 20 package.

Results: The overall P. falciparum prevalence was 31.6%. Half of the malaria positive cases occurred in age group 5 to 14 years. Previous malaria treatment, population density and age group were significant predictors for the model. The model explained 13.5% of the variance in malaria positive cases and sensitivity of the final model was 73.3%.

Conclusion: In this area the highest burden of P. falciparum infection was among those aged 5–14 years old. Malaria infection was related to sociodemographic factors. Targeting malaria control at community level can combat the disease more effectively than waiting for cases at health centers. These finding can be used to guide more effective interventions in this region.

Risk factors for malaria in high incidence areas of Viet Nam: a case-control study

Background

A key step to advancing the goal of malaria elimination in Viet Nam by 2030 is focusing limited resources for treatment and prevention to groups most at risk for malaria transmission.

Methods

To better understand risk factors for malaria transmission in central Viet Nam, a survey of 1000 malaria positive cases and 1000 malaria negative controls was conducted. Cases and controls were matched for age and gender and self-presented at commune health stations (CHS) in Binh Phuoc, Dak Nong and Dak Lak Provinces. Diagnoses were confirmed with microscopy, rapid diagnostic test and PCR. Participants were interviewed about 50 potential risk factors for malaria, which included information about occupation, forest visitation, travel, healthcare-seeking behaviour and prior use of anti-malaria interventions. Participants were enrolled by trained government health workers and the samples were analysed in Vietnamese government laboratories. Data were analysed by univariable, block-wise and multivariable logistic regression.

Results

Among cases, 61.8% had Plasmodium falciparum, 35.2% Plasmodium vivax and 3% mixed species infections. Median (IQR) age was 27 (21–36) years and 91.2% were male. Twenty-five risk factors were associated with being a case and eleven with being a control. Multivariable analysis found that malaria cases correlated with forest workers, recent forest visitation, longer duration of illness, having a recorded fever, number of malaria infections in the past year, having had prior malaria treatment and having previously visited a clinic.

Conclusions

This study demonstrates the benefits of increased statistical power from matched controls in malaria surveillance studies, which allows identification of additional independent risk factors. It also illustrates an example of research partnership between academia and government to collect high quality data relevant to planning malaria elimination activities. Modifiable risk factors and implications of the findings for malaria elimination strategy are presented.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03908-7.

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.

Spatial and Temporal Patterns of Malaria in Phu Yen Province, Vietnam, from 2005 to 2016

Malaria in Vietnam has become focal to a few provinces, including Phu Yen. This study aimed to assess correlations between intervention (population proportion protected by insecticide-treated nets and indoor residual spraying) and climatic variables with malaria incidence in Phu Yen Province. The Vietnam National Institute of Malariology, Parasitology, and Entomology provided incidence data for Plasmodium falciparum and Plasmodium vivax for 104 communes of Phu Yen Province from January 2005 to December 2016. A multivariable, zero-inflated Poisson regression model was developed with a conditional autoregressive prior structure to identify the underlying spatial structure of the data and quantify associations with covariates. There were a total of 2,778 P. falciparum and 1,770 P. vivax cases during the study period. Plasmodium falciparum and P. vivax incidence increased by 5.4% (95% credible interval [CrI] 5.1%, 5.7%) and 3.2% (95% CrI 2.9%, 3.5%) for a 10-mm increase in precipitation without lag, respectively. Plasmodium falciparum and P. vivax incidence decreased by 7.7% (95% CrI 5.6%, 9.7%) and 10.5% (95% CrI 8.3%, 12.6%) for a 1°C increase in minimum temperature without lag, respectively. There was a > 95% probability of a higher than provincial average trend of P. falciparum and P. vivax in Song Cau and Song Hoa districts. There was a > 95% probability of a lower than provincial average trend in Tuy Dong Xuan and Hoa districts for both species. Targeted distribution of resources, including intensified interventions, in this part of the province will be required for local malaria elimination.

Targeting high risk forest goers for malaria elimination: a novel approach for investigating forest malaria to inform program intervention in Vietnam

Background

Individuals that work and sleep in remote forest and farm locations in the Greater Mekong Subregion continue to remain at high risk of both acquiring and transmitting malaria. These difficult-to-access population groups largely fall outside the reach of traditional village-centered interventions, presenting operational challenges for malaria programs. In Vietnam, over 60% of malaria cases are thought to be individuals who sleep in forests or on farms. New malaria elimination strategies are needed in countries where mobile and migrant workers frequently sleep outside of their homes. The aim of this study was to apply targeted surveillance-response based investigative approaches to gather location-specific data on confirmed malaria cases, with an objective to identify associated malaria prevention, treatment and risk behaviors of individuals sleeping in remote forest and farms sites in Vietnam.

Methods

A cross-sectional study using novel targeted reactive investigative approaches at remote area sleeping sites was conducted in three mountainous communes in Phu Yen province in 2016. Index cases were defined as individuals routinely sleeping in forests or farms who had tested positive for malaria. Index cases and non-infected neighbors from forest and farm huts within 500 m of the established sleeping locations of index cases were interviewed at their remote-area sleeping sites.

Results

A total of 307 participants, 110 index cases and 197 neighbors, were enrolled. Among 93 participants who slept in the forest, index cases were more likely to make > 5 trips to the forest per year (prevalence odds ratio (POR) 7.41, 95% confidence interval (CI) 2.66–20.63), sleep in huts without walls (POR 44.00, 95% CI 13.05–148.33), sleep without mosquito nets (POR 2.95, 95% CI 1.26–6.92), and work after dark (POR 5.48, 95% CI 1.84–16.35). Of the 204 farm-based respondents, a significantly higher proportion of index cases were involved in non-farming activities (logging) (POR 2.74, 95% CI 1.27–5.91).

Conclusion

Investigative approaches employed in this study allowed for the effective recruitment and characterization of high-priority individuals frequently sleeping in remote forest and farm locations, providing relevant population and site-specific data that decision makers can use to design and implement targeted interventions to support malaria elimination.

Emerging infectious disease, the household built environment characteristics, and urban planning: Evidence on avian influenza in Vietnam

Recent concerns with pandemic outbreaks of human disease and their origins in animal populations have ignited concerns regarding connections between Emerging Infectious Diseases (EID) and development. As disasters, health, and infectious disease become part of planning concern (Matthew & McDonald, 2007), greater focus on household infrastructure and EID disease outbreaks among poultry is warranted. Following Spencer (2013), this study examines the relationship between the mix of household-scale water supplies, sanitation systems, and construction materials, and Highly Pathogenic Avian Influenza (HPAI) among poultry in a developing country: Vietnam. Findings of our multivariate logistic regressions suggest that a non-linear, Kuznets-shaped urban transition (Spencer, 2013) has an independent effect on the outbreak of HPAI, especially as it relates to household-level sanitation infrastructure. We conclude that the Kuznets-shape development of household infrastructure characteristics in Vietnam play a significant role in explaining where poultry outbreaks occur. Using secondary data from the Census of Population and Housing, and the Agricultural Census at the District and Commune levels for the country of Vietnam, we performed logistic regression to test the relationship between outbreaks of HPAI in poultry and newly-developed "coherence indices" (Spencer, 2013) of household water supply, sanitation, and construction materials that measure nonlinear, transitional development. Results show that district-scale coherence indices are negatively and independently correlated with HPAI outbreaks, especially for sanitation. Findings also suggest that community-scale coherence of urban infrastructures is a powerful tool for predicting where HPAI poultry outbreaks are likely to occur, thereby providing health planners new tools for efficient surveillance.

Risk factor assessment for clinical malaria among forest-goers in a pre-elimination setting in Phu Yen Province, Vietnam

Background

The transition from malaria control to elimination requires understanding and targeting interventions among high-risk populations. In Vietnam, forest-goers are often difficult to test, treat and follow-up for malaria because they are highly mobile. If undiagnosed, forest-goers can maintain parasite reservoirs and contribute to ongoing malaria transmission.

Methods

A case–control study was conducted to identify malaria risk factors associated with forest-goers in three communes in Phu Yen Province, Vietnam. Cases (n = 81) were residents from the study area diagnosed with malaria and known to frequent forest areas. Controls (n = 94) were randomly selected forest-going residents from within the study area with no identified malaria infection. Participants were interviewed face-to-face using a standard questionnaire to identify malaria risk factors. Logistic regression was used to calculate odds ratios (ORs) and 95% CI for risk factors after adjusting for socio-demographic characteristics.

Results

Among the cases, malaria infection varied by species: 66.7% were positive for Plasmodium falciparum, 29.6% for Plasmodium vivax, and 3.7% were diagnosed as mixed infection. Cases were less likely than controls to use treated nets (aOR = 0.31; 95% CI 0.12–0.80), work after dark (aOR = 2.93; 95% CI 1.35, 6.34), bath in a stream after dark (aOR = 2.44; 95% CI 1.02–5.88), and collect water after dark (aOR = 1.99; 95% CI 1.02–3.90).

Conclusions

As Vietnam moves toward malaria elimination, these findings can inform behaviour change communication and malaria prevention strategies, incorporating the risk of after-dark and water-related activities, in this priority and difficult-to-access population group.

[Social determination and determinants of malaria: a systematic review, 1980-2018Determinação social e determinantes sociais da malária: revisão sistemática, 1980-2018]

Objetivo.

Describir cómo se ha aplicado el enfoque de la determinación social de la salud en los estudios sobre malaria en el mundo.

Métodos.

Revisión sistemática de los estudios originales publicados entre 1980 y 2018. Se emplearon seis estrategias de búsqueda en diez bases de datos multidisciplinarias, y en las bibliotecas y los repositorios de siete universidades de Brasil, Colombia, Ecuador y Perú. Se siguió la guía PRISMA; la calidad metodológica se evaluó según los criterios de STROBE y se realizó la síntesis cualitativa de los resultados.

Resultados.

Diez estudios publicados entre 1984 y 2017 cumplieron con los criterios de inclusión y exclusión preestablecidos; se identificaron 33 determinantes sociales de la malaria. De los determinantes individuales se halló mayor riesgo de malaria en adultos, personas con hábitos nocturnos y sin prácticas preventivas; de los intermedios, fueron las viviendas con mala infraestructura física y sanitaria, hacinamiento, ubicadas en áreas boscosas y con animales. De los socioeconómicos, el mayor riesgo correspondió a personas con actividades agroforestales, migrantes, y con bajos ingresos y escolaridad. La malaria ocasionó elevadas pérdidas económicas y generó pobreza y retardo educativo.

Conclusión.

No se hallaron estudios con los enfoques de la Medicina Social Latinoamericana ni que aplicaran el análisis jerárquico y multinivel para los determinantes individuales, intermedios y estructurales, de la Organización Mundial de la Salud. No se ha logrado avanzar en el análisis de categorías sociales —territorio, clase social, género, etnia, políticas macroeconómicas— u otras características socioeconómicas que determinan el riesgo de enfermar o morir de malaria.

Effects of Socio-Environmental Factors on Malaria Infection in Pakistan: A Bayesian Spatial Analysis

The role of socio-environmental factors in shaping malaria dynamics is complex and inconsistent. Effects of socio-environmental factors on malaria in Pakistan at district level were examined. Annual malaria cases data were obtained from Directorate of Malaria Control Program, Pakistan. Meteorological data were supplied by Pakistan Meteorological Department. A major limitation was the use of yearly, rather than monthly/weekly malaria data in this study. Population data, socio-economic data and education score data were downloaded from internet. Bayesian conditional autoregressive model was used to find the statistical association of socio-environmental factors with malaria in Pakistan. From 136/146 districts in Pakistan, >750,000 confirmed malaria cases were included, over a three years' period (2013-2015). Socioeconomic status ((posterior mean value -3.965, (2.5% quintile, -6.297%), (97.5% quintile, -1.754%)) and human population density (-7.41 × 10-4, -0.001406%, -1.05 × 10-4 %) were inversely related, while minimum temperature (0.1398, 0.05275%, 0.2145%) was directly proportional to malaria in Pakistan during the study period. Spatial random effect maps presented that moderate relative risk (RR, 0.75 to 1.24) and high RR (1.25 to 1.99) clusters were scattered throughout the country, outnumbering the ones' with low RR (0.23 to 0.74). Socio-environmental variables influence annual malaria incidence in Pakistan and needs further evaluation.

Social determinants of malaria in an endemic area of Indonesia

Background

Malaria is an increasing concern in Indonesia. Socio-demographic factors were found to strongly influence malaria prevalence. This research aimed to explore the associations between socio-demographic factors and malaria prevalence in Indonesia.

Methods

The study used a cross-sectional design and analysed relationships among the explanatory variables of malaria prevalence in five endemic provinces using multivariable logistic regression.

Results

The analysis of baseline socio-demographic data revealed the following independent risk variables related to malaria prevalence: gender, age, occupation, knowledge of the availability of healthcare services, measures taken to protect from mosquito bites, and housing condition of study participants. Multivariable analysis showed that participants who were unaware of the availability of health facilities were 4.2 times more likely to have malaria than those who were aware of the health facilities (adjusted odds ratio = 4.18; 95% CI 1.52–11.45; P = 0.005).

Conclusions

Factors that can be managed and would favour malaria elimination include a range of prevention behaviours at the individual level and using the networks at the community level of primary healthcare centres. This study suggests that improving the availability of a variety of health facilities in endemic areas, information about their services, and access to these is essential.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2760-8) contains supplementary material, which is available to authorized users.

Analysis of clinical malaria disease patterns and trends in Vietnam 2009-2015

BACKGROUND

Viet Nam has made tremendous progress towards reducing mortality and morbidity associated with malaria in recent years. Despite the success in malaria control, there has been a recent increase in cases in some provinces. In order to understand the changing malaria dynamics in Viet Nam and measure progress towards elimination, the aim of this study was to describe and quantify spatial and temporal trends of malaria by species at district level across the country.

METHODS

Malaria case reports at the Viet Nam National Institute of Malariology, Parasitology, and Entomology were reviewed for the period of January 2009 to December 2015. The population of each district was obtained from the Population and Housing Census-2009. A multivariate (insecticide-treated mosquito nets [ITN], indoor residual spraying [IRS], maximum temperature), zero-inflated, Poisson regression model was developed with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. Covariates included in the models were coverage of intervention (ITN and IRS) and maximum temperature.

RESULTS

There was a total of 57,713 Plasmodium falciparum and 32,386 Plasmodium vivax cases during the study period. The ratio of P. falciparum to P. vivax decreased from 4.3 (81.0% P. falciparum; 11,121 cases) in 2009 to 0.8 (45.0% P. falciparum; 3325 cases) in 2015. Coverage of ITN was associated with decreased P. falciparum incidence, with a 1.1% (95% credible interval [CrI] 0.009%, 1.2%) decrease in incidence for 1% increase in the ITN coverage, but this was not the case for P. vivax, nor was it the case for IRS coverage. Maximum temperature was associated with increased incidence of both species, with a 4% (95% CrI 3.5%, 4.3%) and 1.6% (95% CrI 0.9%, 2.0%) increase in P. falciparum and P. vivax incidence for a temperature increase of 1 °C, respectively. Temporal trends of P. falciparum and P. vivax incidence were significantly higher than the national average in Central and Central-Southern districts.

CONCLUSION

Interventions (ITN distribution) and environmental factors (increased temperature) were associated with incidence of P. falciparum and P. vivax during the study period. The factors reviewed were not exhaustive, however the data suggest distribution of resources can be targeted to areas and times of increased malaria transmission. Additionally, changing distribution of the two predominant malaria species in Viet Nam will require different programmatic approaches for control and elimination.

Malaria transmission trends and its lagged association with climatic factors in the highlands of Plateau State, Nigeria

Background:

Malaria is a serious disease and still remains a public health problem in many parts of Nigeria.

Objectives:

The aim of this study was to describe malaria transmission trends and analyzed the impact of climatic factors on malaria transmission in the highlands of Plateau State, Central Nigeria.

Methods:

The study was a retrospective survey which used archival data of climate parameters and medical case records on malaria. Rainfall, relative humidity, and temperature data were obtained from the nearest weather stations to the study locations from 1980 to 2015. Data on reported malaria cases were collected from general hospitals in the selected local government areas (LGAs) from 2003 to 2015. Generalized Additive Models were used to model trends in malaria incidences over time, and it is lagged association with climatic factors.

Results:

The results show a significant cyclical trend in malaria incidence in all the study areas (P < 0.001). The association between monthly malaria cases and mean monthly temperature, rainfall, and relative humidity show significant association at different time lags and locations.

Conclusion:

Our findings suggest that climatic factors are among the major determinants of malaria transmission in the highlands of Plateau state except in Jos-North LGA where the low model deviance explained (35.4%) could mean that there are other important factors driving malaria transmission in the area other than climatic factors.

Paleopathological Considerations on Malaria Infection in Korea before the 20th Century

Malaria, one of the deadliest diseases in human history, still infects many people worldwide. Among the species of the genus Plasmodium, P. vivax is commonly found in temperate-zone countries including South Korea. In this article, we first review the history of malarial infection in Korea by means of studies on Joseon documents and the related scientific data on the evolutionary history of P. vivax in Asia. According to the historical records, malarial infection was not unusual in pre-20th-century Korean society. We also found that certain behaviors of the Joseon people might have affected the host-vector-pathogen relationship, which could explain why malarial infection prevalence was so high in Korea at that time. In our review of genetic studies on P. vivax, we identified substantial geographic differentiation among continents and even between neighboring countries. Based on these, we were able to formulate a strategy for future analysis of ancient Plasmodium strains in Korea.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys

Background

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted.

Methods

Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty.

Findings

Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7–79.4) for the 2015 Kenya MIS (estimated sample size of children 0–4 years 7218 [7099–7288]), and 54.1% [50.1–56.5] for the 2014–2015 Rwanda DHS (12,220 [11,950–12,410]).

Conclusion

This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

Electronic supplementary material

The online version of this article (10.1186/s12936-017-2127-y) contains supplementary material, which is available to authorized users.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover (p < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

BACKGROUND

The world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management. Interestingly India, as opposed to Africa, harbors a mosquito vector, Anopheles stephensi, which thrives in the man-made environments of cities and acts as the vector for both Plasmodium vivax and Plasmodium falciparum, making the malaria problem a truly urban phenomenon. Here we address the role and determinants of within-city spatial heterogeneity in the incidence patterns of vivax malaria, and then draw comparisons with results for falciparum malaria.

METHODOLOGY/PRINCIPAL FINDINGS

Statistical analyses and a phenomenological transmission model are applied to an extensive spatio-temporal dataset on cases of Plasmodium vivax in the city of Ahmedabad (Gujarat, India) that spans 12 years monthly at the level of wards. A spatial pattern in malaria incidence is described that is largely stationary in time for this parasite. Malaria risk is then shown to be associated with socioeconomic indicators and environmental parameters, temperature and humidity. In a more dynamical perspective, an Inhomogeneous Markov Chain Model is used to predict vivax malaria risk. Models that account for climate factors, socioeconomic level and population size show the highest predictive skill. A comparison to the transmission dynamics of falciparum malaria reinforces the conclusion that the spatio-temporal patterns of risk are strongly driven by extrinsic factors.

CONCLUSION/SIGNIFICANCE

Climate forcing and socio-economic heterogeneity act synergistically at local scales on the population dynamics of urban malaria in this city. The stationarity of malaria risk patterns provides a basis for more targeted intervention, such as vector control, based on transmission 'hotspots'. This is especially relevant for P. vivax, a more resilient parasite than P. falciparum, due to its ability to relapse and the operational shortcomings of delivering a "radical cure".

Temporal and spatial changes in persistent organic pollutants in Vietnamese coastal waters detected from plastic resin pellets

Plastic resin pellets collected at Minh Chau island and Ba Lat estuary between 2007 and 2014 in Vietnam were analyzed for dichloro-diphenyl-trichloroethanes (DDTs), polychlorinated biphenyls (PCBs) and hexachlorocyclohexanes (HCHs). The study was carried out as part of the International Pellet Watch program for monitoring the global distribution of persistent organic pollutants (POPs). Higher levels of DDTs compared to PCBs indicated agricultural inputs rather than industrial discharges in the region. Most POP concentrations on both beaches decreased over the period, with the exception of HCH isomers. Though the concentration of DDTs showed a drastic decline on both beaches between 2007/2008 and 2014, DDTs accounted for 60-80% of total DDTs, suggesting that there is still a fresh input of these chemicals in the region. This study strongly recommends further investigations to track temporal and spatial patterns of POP levels in the marine environment using plastic resin pellets.

Geography and social distribution of malaria in Indonesian Papua: a cross-sectional study

Background

Despite being one of the world’s most affected regions, only little is known about the social and spatial distributions of malaria in Indonesian Papua. Existing studies tend to be descriptive in nature; their inferences are prone to confounding and selection biases. At the same time, there remains limited malaria-cartographic activity in the region. Analysing a subset (N = 22,643) of the National Basic Health Research 2007 dataset (N = 987,205), this paper aims to quantify the district-specific risk of malaria in Papua and to understand how socio-demographic/economic factors measured at individual and district levels are associated with individual’s probability of contracting the disease.

Methods

We adopt a Bayesian hierarchical logistic regression model that accommodates not only the nesting of individuals within the island’s 27 administrative units but also the spatial autocorrelation among these locations. Both individual and contextual characteristics are included as predictors in the model; a normal conditional autoregressive prior and an exchangeable one are assigned to the random effects. Robustness is then assessed through sensitivity analyses using alternative hyperpriors.

Results

We find that rural Papuans as well as those who live in poor, densely forested, lowland districts are at a higher risk of infection than their counterparts. We also find age and gender differentials in malaria prevalence, if only to a small degree. Nine districts are estimated to have higher-than-expected malaria risks; the extent of spatial variation on the island remains notable even after accounting for socio-demographic/economic risk factors.

Conclusions

Although we show that malaria is geography-dependent in Indonesian Papua, it is also a disease of poverty. This means that malaria eradication requires not only biological (proximal) interventions but also social (distal) ones.

Malaria and the mobile and migrant population in Cambodia: a population movement framework to inform strategies for malaria control and elimination

BACKGROUND

The relationships between human population movement (HPM) and health are a concern at global level. In the case of malaria, those links are crucial in relation to the spread of drug resistant parasites and to the elimination of malaria in the Greater Mekong sub-Region (GMS) and beyond. The mobile and migrant populations (MMP) who are involved in forest related activities are both at high risk of being infected with malaria and at risk of receiving late and sub-standard treatment due to poor access to health services. In Cambodia, in 2012, the National Malaria Control Programme (NMCP) identified, as a key objective, the development of a specific strategy for MMPs in order to address these challenges. A population movement framework (PMF) for malaria was developed and operationalized in order to contribute to this strategy.

METHODS

A review of the published and unpublished literature was conducted. Based on a synthesis of the results, information was presented and discussed with experienced researchers and programme managers in the Cambodian NMCP and led to the development and refinement of a PMF for malaria. The framework was "tested" for face and content validity with national experts through a workshop approach.

RESULTS

In the literature, HPM has been described using various spatial and temporal dimensions both in the context of the spread of anti-malarial drug resistance, and in the context of malaria elimination and previous classifications have categorized MMPs in Cambodia and the GMS through using a number of different criteria. Building on these previous models, the PMF was developed and then refined and populated with in-depth information relevant to Cambodia collected from social science research and field experiences in Cambodia. The framework comprises of the PMF itself, MMP activity profiles and a Malaria Risk Index which is a summation of three related indices: a vulnerability index, an exposure index and an access index which allow a qualitative ranking of malaria risk in the MMP population. Application of currently available data to the framework illustrates that the highest risk population are those highly mobile populations engaged in forest work.

CONCLUSION

This paper describes the process of defining MMPs in Cambodia, identifying the different activities and related risks to appropriately target and tailor interventions to the highest risk groups. The framework has been used to develop more targeted behaviour change and outreach interventions for MMPs in Cambodia and its utility and effectiveness will be evaluated as part of those interventions.

Cross-border malaria: a major obstacle for malaria elimination

Movement of malaria across international borders poses a major obstacle to achieving malaria elimination in the 34 countries that have committed to this goal. In border areas, malaria prevalence is often higher than in other areas due to lower access to health services, treatment-seeking behaviour of marginalized populations that typically inhabit border areas, difficulties in deploying prevention programmes to hard-to-reach communities, often in difficult terrain, and constant movement of people across porous national boundaries. Malaria elimination in border areas will be challenging and key to addressing the challenges is strengthening of surveillance activities for rapid identification of any importation or reintroduction of malaria. This could involve taking advantage of technological advances, such as spatial decision support systems, which can be deployed to assist programme managers to carry out preventive and reactive measures, and mobile phone technology, which can be used to capture the movement of people in the border areas and likely sources of malaria importation. Additionally, joint collaboration in the prevention and control of cross-border malaria by neighbouring countries, and reinforcement of early diagnosis and prompt treatment are ways forward in addressing the problem of cross-border malaria.

Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks

Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource-based habitat concept (RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector-borne pathogens is explored and illustrated with the case of bluetongue virus, a midge-transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches.

Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006-2009

BACKGROUND

Identifying areas that support high malaria risks and where populations lack access to health care is central to reducing the burden in Afghanistan. This study investigated the incidence of Plasmodium vivax and Plasmodium falciparum using routine data to help focus malaria interventions.

METHODS

To estimate incidence, the study modelled utilisation of the public health sector using fever treatment data from the 2012 national Malaria Indicator Survey. A probabilistic measure of attendance was applied to population density metrics to define the proportion of the population within catchment of a public health facility. Malaria data were used in a Bayesian spatio-temporal conditional-autoregressive model with ecological or environmental covariates, to examine the spatial and temporal variation of incidence.

FINDINGS

From the analysis of healthcare utilisation, over 80% of the population was within 2 hours' travel of the nearest public health facility, while 64.4% were within 30 minutes' travel. The mean incidence of P. vivax in 2009 was 5.4 (95% Crl 3.2-9.2) cases per 1000 population compared to 1.2 (95% Crl 0.4-2.9) cases per 1000 population for P. falciparum. P. vivax peaked in August while P. falciparum peaked in November. 32% of the estimated 30.5 million people lived in regions where annual incidence was at least 1 case per 1,000 population of P. vivax; 23.7% of the population lived in areas where annual P. falciparum case incidence was at least 1 per 1000.

CONCLUSION

This study showed how routine data can be combined with household survey data to model malaria incidence. The incidence of both P. vivax and P. falciparum in Afghanistan remain low but the co-distribution of both parasites and the lag in their peak season provides challenges to malaria control in Afghanistan. Future improved case definition to determine levels of imported risks may be useful for the elimination ambitions in Afghanistan.

Modelling the effects of weather and climate on malaria distributions in West Africa

Background

Malaria is a leading cause of mortality worldwide. There is currently conflicting data and interpretation on how variability in climate factors affects the incidence of malaria. This study presents a hierarchical Bayesian modelling framework for the analysis of malaria versus climate factors in West Africa.

Methods

The hierarchical Bayesian framework takes into account spatiotemporal dependencies, and in this paper is applied to annual malaria and climate data from ten West African countries (Benin, Burkina Faso, Côte d'Ivoire, Gambia, Ghana, Liberia, Mali, Senegal, Sierra Leone, and Togo) during the period 1996-2006.

Results

Results show a statistically significant correspondence between malaria rates and the climate variables considered. The two most important climate factors are found to be average annual temperature and total annual precipitation, and they show negative association with malaria incidence.

Conclusions

This modelling framework provides a useful approach for studying the impact of climate variability on the spread of malaria and may help to resolve some conflicting interpretations in the literature.

Spatial trend, environmental and socioeconomic factors associated with malaria prevalence in Chennai

Background

Urban malaria is considered to be one of the most significant infectious diseases due to varied socioeconomic problems especially in tropical countries like India. Among the south Indian cities, Chennai is endemic for malaria. The present study aimed to identify the hot spots of malaria prevalence and the relationship with other factors in Chennai during 2005-2011.

Methods

Data on zone-wise and ward-wise monthly malaria positive cases were collected from the Vector Control Office, Chennai Corporation, for the year 2005 to 2011 and verified using field data. This data was used to calculate the prevalence among thousand people. Hotspot analysis for all the years in the study period was done to observe the spatial trend. Association of environmental factors like altitude, population density and climatic variables was assessed using ArcGIS 9.3 version and SPSS 11.5. Pearson’s correlation of climate parameters at 95% and 99% was considered to be the most significant. Social parameters of the highly malaria prone region were evaluated through a structured random questionnaire field survey.

Results

Among the ten zones of Chennai Corporation, Basin Bridge zone showed high malaria prevalence during the study period. The ‘hotspot’ analysis of malaria prevalence showed the emergence of newer hotspots in the Adyar zone. These hotspots of high prevalence are places of moderately populated and moderately elevated areas. The prevalence of malaria in Chennai could be due to rainfall and temperature, as there is a significant correlation with monthly rainfall and one month lag of monthly mean temperature. Further it has been observed that the socioeconomic status of people in the malaria hotspot regions and unhygienic living conditions were likely to aggravate the malaria problem.

Conclusion

Malaria hotspots will be the best method to use for targeting malaria control activities. Proper awareness and periodical monitoring of malaria is one of the quintessential steps to control this infectious disease. It has been argued that identifying the key environmental conditions favourable for the occurrence and spread of malaria must be integrated and documented to aid future predictions of malaria in Chennai.

Plasmodium vivax malaria incidence over time and its association with temperature and rainfall in four counties of Yunnan Province, China

BACKGROUND

Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China.

METHODS

Plasmodium vivax malaria surveillance data (1991-2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence.

RESULTS

There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas.

CONCLUSIONS

The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.

Analysis of partial and complete protection in malaria cohort studies

Background

Malaria transmission is highly heterogeneous and analysis of incidence data must account for this for correct statistical inference. Less widely appreciated is the occurrence of a large number of zero counts (children without a malaria episode) in malaria cohort studies. Zero-inflated regression methods provide one means of addressing this issue, and also allow risk factors providing complete and partial protection to be disentangled.

Methods

Poisson, negative binomial (NB), zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) regression models were fitted to data from two cohort studies of malaria in children in Ghana. Multivariate models were used to understand risk factors for elevated incidence of malaria and for remaining malaria-free, and to estimate the fraction of the population not at risk of malaria.

Results

ZINB models, which account for both heterogeneity in individual risk and an unexposed sub-group within the population, provided the best fit to data in both cohorts. These approaches gave additional insight into the mechanism of factors influencing the incidence of malaria compared to simpler approaches, such as NB regression. For example, compared to urban areas, rural residence was found to both increase the incidence rate of malaria among exposed children, and increase the probability of being exposed. In Navrongo, 34% of urban residents were estimated to be at no risk, compared to 3% of rural residents. In Kintampo, 47% of urban residents and 13% of rural residents were estimated to be at no risk.

Conclusion

These results illustrate the utility of zero-inflated regression methods for analysis of malaria cohort data that include a large number of zero counts. Specifically, these results suggest that interventions that reach mainly urban residents will have limited overall impact, since some urban residents are essentially at no risk, even in areas of high endemicity, such as in Ghana.

Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial-temporal models

As malaria transmission declines, it becomes increasingly important to monitor changes in malaria incidence rather than prevalence. Here, a spatio-temporal model was used to identify constituencies with high malaria incidence to guide malaria control. Malaria cases were assembled across all age groups along with several environmental covariates. A Bayesian conditional-autoregressive model was used to model the spatial and temporal variation of incidence after adjusting for test positivity rates and health facility utilisation. Of the 144,744 malaria cases recorded in Namibia in 2009, 134,851 were suspected and 9893 were parasitologically confirmed. The mean annual incidence based on the Bayesian model predictions was 13 cases per 1000 population with the highest incidence predicted for constituencies bordering Angola and Zambia. The smoothed maps of incidence highlight trends in disease incidence. For Namibia, the 2009 maps provide a baseline for monitoring the targets of pre-elimination.

Spatial parasite ecology and epidemiology: a review of methods and applications

The distributions of parasitic diseases are determined by complex factors, including many that are distributed in space. A variety of statistical methods are now readily accessible to researchers providing opportunities for describing and ultimately understanding and predicting spatial distributions. This review provides an overview of the spatial statistical methods available to parasitologists, ecologists and epidemiologists and discusses how such methods have yielded new insights into the ecology and epidemiology of infection and disease. The review is structured according to the three major branches of spatial statistics: continuous spatial variation; discrete spatial variation; and spatial point processes.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION

Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using bayesian spatiotemporal methods.

METHODS

We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed.

RESULTS

The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases.

CONCLUSIONS

It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the bayesian paradigm is a good strategy for modeling malaria counts.

Malaria ecotypes and stratification

To deal with the variability of malaria, control programmes need to stratify their malaria problem into a number of smaller units. Such stratification may be based on the epidemiology of malaria or on its determinants such as ecology. An ecotype classification was developed by the World Health Organization (WHO) around 1990, and it is time to assess its usefulness for current malaria control as well as for malaria modelling on the basis of published research. Journal and grey literature was searched for articles on malaria or Anopheles combined with ecology or stratification. It was found that all malaria in the world today could be assigned to one or more of the following ecotypes: savanna, plains and valleys; forest and forest fringe; foothill; mountain fringe and northern and southern fringes; desert fringe; coastal and urban. However, some areas are in transitional or mixed zones; furthermore, the implications of any ecotype depend on the biogeographical region, sometimes subregion, and finally, the knowledge on physiography needs to be supplemented by local information on natural, anthropic and health system processes including malaria control. Ecotyping can therefore not be seen as a shortcut to determine control interventions, but rather as a framework to supplement available epidemiological and entomological data so as to assess malaria situations at the local level, think through the particular risks and opportunities and reinforce intersectoral action. With these caveats, it does however emerge that several ecotypic distinctions are well defined and have relatively constant implications for control within certain biogeographic regions. Forest environments in the Indo-malay and the Neotropics are, with a few exceptions, associated with much higher malaria risk than in adjacent areas; the vectors are difficult to control, and the anthropic factors also often converge to impose constraints. Urban malaria in Africa is associated with lower risk than savanna malaria; larval control may be considered though its role is not so far well established. In contrast, urban malaria in the Indian subcontinent is associated with higher risks than most adjacent rural areas, and larval control has a definite, though not exclusive, role. Simulation modelling of cost-effectiveness of malaria control strategies in different scenarios should prioritize ecotypes where malaria control encounters serious technical problems. Further field research on malaria and ecology should be interdisciplinary, especially with geography, and pay more attention to juxtapositions and to anthropic elements, especially migration.

Characterizing the spatial and temporal variation of malaria incidence in Bangladesh, 2007

Background

Malaria remains a significant health problem in Bangladesh affecting 13 of 64 districts. The risk of malaria is variable across the endemic areas and throughout the year. A better understanding of the spatial and temporal patterns in malaria risk and the determinants driving the variation are crucial for the appropriate targeting of interventions under the National Malaria Control and Prevention Programme.

Methods

Numbers of Plasmodium falciparum and Plasmodium vivax malaria cases reported by month in 2007, across the 70 endemic thanas (sub-districts) in Bangladesh, were assembled from health centre surveillance reports. Bayesian Poisson regression models of incidence were constructed, with fixed effects for monthly rainfall, maximum temperature and elevation, and random effects for thanas, with a conditional autoregressive prior spatial structure.

Results

The annual incidence of reported cases was 34.0 and 9.6 cases/10,000 population for P. falciparum and P. vivax respectively and the population of the 70 malaria-endemic thanas was approximately 13.5 million in 2007. Incidence of reported cases for both types of malaria was highest in the mountainous south-east of the country (the Chittagong Hill Tracts). Models revealed statistically significant positive associations between the incidence of reported P. vivax and P. falciparum cases and rainfall and maximum temperature.

Conclusions

The risk of P. falciparum and P. vivax was spatially variable across the endemic thanas of Bangladesh and also highly seasonal, suggesting that interventions should be targeted and timed according to the risk profile of the endemic areas. Rainfall, temperature and elevation are major factors driving the spatiotemporal patterns of malaria in Bangladesh.

Plasmodium vivax malaria endemicity in Indonesia in 2010

Background

Plasmodium vivax imposes substantial morbidity and mortality burdens in endemic zones. Detailed understanding of the contemporary spatial distribution of this parasite is needed to combat it. We used model based geostatistics (MBG) techniques to generate a contemporary map of risk of Plasmodium vivax malaria in Indonesia in 2010.

Methods

Plasmodium vivax Annual Parasite Incidence data (2006–2008) and temperature masks were used to map P. vivax transmission limits. A total of 4,658 community surveys of P. vivax parasite rate (PvPR) were identified (1985–2010) for mapping quantitative estimates of contemporary endemicity within those limits. After error-checking a total of 4,457 points were included into a national database of age-standardized 1–99 year old PvPR data. A Bayesian MBG procedure created a predicted PvPR_1–99 endemicity surface with uncertainty estimates. Population at risk estimates were derived with reference to a 2010 human population surface.

Results

We estimated 129.6 million people in Indonesia lived at risk of P. vivax transmission in 2010. Among these, 79.3% inhabited unstable transmission areas and 20.7% resided in stable transmission areas. In western Indonesia, the predicted P. vivax prevalence was uniformly low. Over 70% of the population at risk in this region lived on Java and Bali islands, where little malaria transmission occurs. High predicted prevalence areas were observed in the Lesser Sundas, Maluku and Papua. In general, prediction uncertainty was relatively low in the west and high in the east.

Conclusion

Most Indonesians living with endemic P. vivax experience relatively low risk of infection. However, blood surveys for this parasite are likely relatively insensitive and certainly do not detect the dormant liver stage reservoir of infection. The prospects for P. vivax elimination would be improved with deeper understanding of glucose-6-phosphate dehydrogenase deficiency (G6PDd) distribution, anti-relapse therapy practices and manageability of P. vivax importation risk, especially in Java and Bali.

Malaria in the Greater Mekong Subregion: heterogeneity and complexity

The Greater Mekong Subregion (GMS), comprised of six countries including Cambodia, China's Yunnan Province, Lao PDR, Myanmar (Burma), Thailand and Vietnam, is one of the most threatening foci of malaria. Since the initiation of the WHO's Mekong Malaria Program a decade ago, malaria situation in the GMS has greatly improved, reflected in the continuous decline in annual malaria incidence and deaths. However, as many nations are moving towards malaria elimination, the GMS nations still face great challenges. Malaria epidemiology in this region exhibits enormous geographical heterogeneity with Myanmar and Cambodia remaining high-burden countries. Within each country, malaria distribution is also patchy, exemplified by 'border malaria' and 'forest malaria' with high transmission occurring along international borders and in forests or forest fringes, respectively. 'Border malaria' is extremely difficult to monitor, and frequent malaria introductions by migratory human populations constitute a major threat to neighboring, malaria-eliminating countries. Therefore, coordination between neighboring countries is essential for malaria elimination from the entire region. In addition to these operational difficulties, malaria control in the GMS also encounters several technological challenges. Contemporary malaria control measures rely heavily on effective chemotherapy and insecticide control of vector mosquitoes. However, the spread of multidrug resistance and potential emergence of artemisinin resistance in Plasmodium falciparum make resistance management a high priority in the GMS. This situation is further worsened by the circulation of counterfeit and substandard artemisinin-related drugs. In most endemic areas of the GMS, P. falciparum and Plasmodium vivax coexist, and in recent malaria control history, P. vivax has demonstrated remarkable resilience to control measures. Deployment of the only registered drug (primaquine) for the radical cure of vivax malaria is severely undermined due to high prevalence of glucose-6-phosphate dehydrogenase deficiency in target human populations. In the GMS, the dramatically different ecologies, diverse vector systems, and insecticide resistance render traditional mosquito control less efficient. Here we attempt to review the changing malaria epidemiology in the GMS, analyze the vector systems and patterns of malaria transmission, and identify the major challenges the malaria control community faces on its way to malaria elimination.

Malaria in the Greater Mekong Subregion: heterogeneity and complexity

The Greater Mekong Subregion (GMS), comprised of six countries including Cambodia, China's Yunnan Province, Lao PDR, Myanmar (Burma), Thailand and Vietnam, is one of the most threatening foci of malaria. Since the initiation of the WHO's Mekong Malaria Program a decade ago, malaria situation in the GMS has greatly improved, reflected in the continuous decline in annual malaria incidence and deaths. However, as many nations are moving towards malaria elimination, the GMS nations still face great challenges. Malaria epidemiology in this region exhibits enormous geographical heterogeneity with Myanmar and Cambodia remaining high-burden countries. Within each country, malaria distribution is also patchy, exemplified by 'border malaria' and 'forest malaria' with high transmission occurring along international borders and in forests or forest fringes, respectively. 'Border malaria' is extremely difficult to monitor, and frequent malaria introductions by migratory human populations constitute a major threat to neighboring, malaria-eliminating countries. Therefore, coordination between neighboring countries is essential for malaria elimination from the entire region. In addition to these operational difficulties, malaria control in the GMS also encounters several technological challenges. Contemporary malaria control measures rely heavily on effective chemotherapy and insecticide control of vector mosquitoes. However, the spread of multidrug resistance and potential emergence of artemisinin resistance in Plasmodium falciparum make resistance management a high priority in the GMS. This situation is further worsened by the circulation of counterfeit and substandard artemisinin-related drugs. In most endemic areas of the GMS, P. falciparum and Plasmodium vivax coexist, and in recent malaria control history, P. vivax has demonstrated remarkable resilience to control measures. Deployment of the only registered drug (primaquine) for the radical cure of vivax malaria is severely undermined due to high prevalence of glucose-6-phosphate dehydrogenase deficiency in target human populations. In the GMS, the dramatically different ecologies, diverse vector systems, and insecticide resistance render traditional mosquito control less efficient. Here we attempt to review the changing malaria epidemiology in the GMS, analyze the vector systems and patterns of malaria transmission, and identify the major challenges the malaria control community faces on its way to malaria elimination.

Modeling the influence of local environmental factors on malaria transmission in Benin and its implications for cohort study

Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission—even at a very local scale—is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors.

As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages.

This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.

Genetic diversity in the merozoite surface protein 1 and 2 genes of Plasmodium falciparum from the Artibonite Valley of Haiti

Describing genetic diversity of the Plasmodium falciparum parasite provides important information about the local epidemiology of malaria. In this study, we examined the genetic diversity of P. falciparum isolates from the Artibonite Valley in Haiti using the allelic families of merozoite surface protein 1 and 2 genes (msp-1 and msp-2). The majority of study subjects infected with P. falciparum had a single parasite genotype (56% for msp-1 and 69% for msp-2: n=79); 9 distinct msp-1 genotypes were identified by size differences on agarose gels. K1 was the most polymorphic allelic family with 5 genotypes (amplicons from 100 to 300 base pairs [bp]); RO33 was the least polymorphic, with a single genotype (120-bp). Although both msp-2 alleles (3D7/IC1, FC27) had similar number of genotypes (n=4), 3D7/IC1 was more frequent (85% vs. 26%). All samples were screened for the presence of the K76T mutation on the P. falciparum chloroquine resistance transporter (pfcrt) gene with 10 of 79 samples positive. Of the 2 (out of 10) samples from individuals follow-up for 21 days, P. falciparum parasites were present through day 7 after treatment with chloroquine. No parasites were found on day 21. Our results suggest that the level of genetic diversity is low in this area of Haiti, which is consistent with an area of low transmission.

Plasmodium falciparum malaria endemicity in Indonesia in 2010

Background

Malaria control programs require a detailed understanding of the contemporary spatial distribution of infection risk to efficiently allocate resources. We used model based geostatistics (MBG) techniques to generate a contemporary map of Plasmodium falciparum malaria risk in Indonesia in 2010.

Methods

Plasmodium falciparum Annual Parasite Incidence (PfAPI) data (2006–2008) were used to map limits of P. falciparum transmission. A total of 2,581 community blood surveys of P. falciparum parasite rate (PfPR) were identified (1985–2009). After quality control, 2,516 were included into a national database of age-standardized 2–10 year old PfPR data (PfPR_2–10) for endemicity mapping. A Bayesian MBG procedure was used to create a predicted surface of PfPR_2–10 endemicity with uncertainty estimates. Population at risk estimates were derived with reference to a 2010 human population count surface.

Results

We estimate 132.8 million people in Indonesia, lived at risk of P. falciparum transmission in 2010. Of these, 70.3% inhabited areas of unstable transmission and 29.7% in stable transmission. Among those exposed to stable risk, the vast majority were at low risk (93.39%) with the reminder at intermediate (6.6%) and high risk (0.01%). More people in western Indonesia lived in unstable rather than stable transmission zones. In contrast, fewer people in eastern Indonesia lived in unstable versus stable transmission areas.

Conclusion

While further feasibility assessments will be required, the immediate prospects for sustained control are good across much of the archipelago and medium term plans to transition to the pre-elimination phase are not unrealistic for P. falciparum. Endemicity in areas of Papua will clearly present the greatest challenge. This P. falciparum endemicity map allows malaria control agencies and their partners to comprehensively assess the region-specific prospects for reaching pre-elimination, monitor and evaluate the effectiveness of future strategies against this 2010 baseline and ultimately improve their evidence-based malaria control strategies.

Polymorphism of Plasmodium falciparum Na(+)/H(+) exchanger is indicative of a low in vitro quinine susceptibility in isolates from Viet Nam

Background

The Plasmodium falciparum NA+/H+ exchanger (pfnhe1, gene PF13_0019) has recently been proposed to influence quinine (QN) susceptibility. However, its contribution to QN resistance seems to vary geographically depending on the genetic background of the parasites. Here, the role of this gene was investigated in in vitro QN susceptibility of isolates from Viet Nam.

Method

Ninety-eight isolates were obtained from three different regions of the Binh Phuoc and Dak Nong bordering Cambodia provinces during 2006-2008. Among these, 79 were identified as monoclonal infection and were genotyped at the microsatellite pfnhe1 ms4760 locus and in vitro QN sensitivity data were obtained for 51 isolates. Parasite growth was assessed in the field using the HRP2 immunodetection assay.

Results

Significant associations were found between polymorphisms at pfnhe1 microsatellite ms4760 and susceptibility to QN. Isolates with two or more DNNND exhibited much lower susceptibility to QN than those harbouring zero or one DNNND repeats (median IC₅₀ of 682 nM versus median IC₅₀ of 300 nM; p = 0.0146) while isolates with one NHNDNHNNDDD repeat presented significantly reduced QN susceptibility than those who had two (median IC₅₀ of 704 nM versus median IC₅₀ of 375 nM; p < 0.01). These QNR associated genotype features were mainly due to the over representation of profile 7 among isolates (76.5%). The majority of parasites had pfcrt76T and wild-type pfmdr1 (> 95%) thus preventing analysis of associations with these mutations. Interestingly, area with the highest median QN IC₅₀ showed also the highest percentage of isolates carrying the pfnhe1 haplotype 7.

Conclusions

The haplotype 7 which is the typical Asian profile is likely well-adapted to high drug pressure in this area and may constitute a good genetic marker to evaluate the dissemination of QNR in this part of the world.

Disease appearance and evolution against a background of climate change and reduced resources

Global health continues to face increasing challenges owing to a variety of reasons that include the almost constant changes in disease appearance and evolution. Most, but not all, of these changes affect low-income countries and are influenced by climate change. Tracking the recent and anticipated changes in the demographics and global distribution of these changes is essential for evolving effective new methods for dealing with the problems. The recent recognition by the United Nations of the importance of non-communicable diseases is a major positive step. For the sake of this paper, the following diseases were chosen: dengue and malaria, to highlight the role of climate change on vector-borne diseases. Drug-resistant tuberculosis illustrates the role of globalization and reduced resources on disease evolution. The continuing rise in cardiovascular mortality and morbidity, particularly in resource-poor countries is largely attributed to lack of preventive and therapeutic measures against such conditions as hypertension, diabetes, atherosclerosis and congenital heart disease as well as neglected diseases, of which Chagas and rheumatic heart disease will be discussed further.