Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia

The impact of climate change on child nutrition in Indonesia: a conceptual framework and scoping review of the available evidence

BACKGROUND

Climate change is expected to significantly impact child nutrition, worsening global health inequities. Indonesia, a country highly vulnerable to climate change, also faces substantial child malnutrition challenges. However, comprehensive knowledge on climate change's impacts on child nutrition in Indonesia is limited. This study addresses this gap through a scoping review of the scientific evidence on the effects of climate change on child nutrition in Indonesia.

METHODS

We developed a conceptual framework based on global literature to guide our systematic search, linking climate change to child nutrition and its determinants in Indonesia. Systematic searches were conducted in English and Indonesian on Scopus, Web of Science and PubMed, supplemented by Google Scholar and citation screening. We included peer-reviewed, Scopus-indexed studies focused on Indonesia, examining either direct or indirect impacts of climate change on child nutrition. A narrative synthesis was performed, structured around outcomes identified in our framework: (1) nutrition-associated conditions, (2) diets and disease, (3) social dynamics and (4) food system shocks.

RESULTS

From 3025 records, 134 studies met the inclusion criteria. Studies were either multicountry including Indonesia (23%, n=31), Indonesia-specific across multiple regions (26%, n=35) or region-specific, mainly focused on Java (22%, n=29), Sumatra (11%, n=14), Kalimantan (7%, n=9) and Sulawesi (7%, n=9). Other regions were under-represented (5%, n=7). Most studies used quantitative methods (87%, n=116). Few studies assessed direct links between climate change and nutritional outcomes (n=5), food security or dietary quality (n=7); more focused on indirect pathways such as disease (n=49), social dynamics (n=18) and food system disruptions (n=55).

CONCLUSIONS

Evidence suggests significant impacts of climate change on child nutrition in Indonesia, highlighting the need for urgent action. Further localised studies that consider contextual factors, and actions focused on strengthening health and nutrition systems, are critical, especially in regions most vulnerable to both climate change and child malnutrition.

Application of multivariate binary logistic regression grouped outlier statistics and geospatial logistic model to identify villages having unusual health-seeking habits for childhood malaria in Malawi

BACKGROUND

Early diagnosis and prompt treatment of malaria in young children are crucial for preventing the serious stages of the disease. If delayed treatment-seeking habits are observed in certain areas, targeted campaigns and interventions can be implemented to improve the situation.

METHODS

This study applied multivariate binary logistic regression model diagnostics and geospatial logistic model to identify traditional authorities in Malawi where caregivers have unusual health-seeking behaviour for childhood malaria. The data from the 2021 Malawi Malaria Indicator Survey were analysed using R software version 4.3.0 for regressions and STATA version 17 for data cleaning.

RESULTS

Both models showed significant variability in treatment-seeking habits of caregivers between villages. The mixed-effects logit model residual identified Vuso Jere, Kampingo Sibande, Ngabu, and Dzoole as outliers in the model. Despite characteristics that promote late reporting of malaria at clinics, most mothers in these traditional authorities sought treatment within twenty-four hours of the onset of malaria symptoms in their children. On the other hand, the geospatial logit model showed that late seeking of malaria treatment was prevalent in most areas of the country, except a few traditional authorities such as Mwakaboko, Mwenemisuku, Mwabulambya, Mmbelwa, Mwadzama, Zulu, Amidu, Kasisi, and Mabuka.

CONCLUSIONS

These findings suggest that using a combination of multivariate regression model residuals and geospatial statistics can help in identifying communities with distinct treatment-seeking patterns for childhood malaria within a population. Health policymakers could benefit from consulting traditional authorities who demonstrated early reporting for care in this study. This could help in understanding the best practices followed by mothers in those areas which can be replicated in regions where seeking care is delayed.

Evaluation of the malaria elimination programme in Muara Enim Regency: a qualitative study from Indonesia

BACKGROUND

Malaria remains an enduring public health concern in Indonesia, exacerbated by its equatorial climate that fosters the proliferation of Anopheles mosquitoes. This study seeks to assess the performance of the malaria elimination programme comprehensively.

METHODS

Between May and August 2022, a qualitative study was conducted in Muara Enim Regency, South Sumatra Province, involving 22 healthcare professionals from diverse backgrounds. These informants were strategically chosen for their pivotal roles in providing profound insights into various facets of the malaria elimination programme. This encompasses inputs such as human resources, budgetary allocation, and infrastructural support; processes like case identification and management, capacity enhancement, epidemiological surveillance, prevention measures, outbreak control, and enhanced communication and educational initiatives; and, notably, the programme's outcomes. Data were collected through 3-h Focus Group Discussions (FGDs) divided into two groups, each with 12 participants: healthcare professionals and programme managers. Additionally, in-depth interviews (IDIs) were conducted with ten informants. Employing the Input-Process-Output (IPO) model, this study meticulously analysed the healthcare system dynamics and the interventions' efficacy.

RESULTS

The study unveiled many challenges during the input phase, including the absence of entomologists and a shortage of diagnostic tools. Despite these obstacles, it documented remarkable accomplishments in the output domain, marked by significant advancements in the distribution of mosquito nets and the successful implementation of the Early Warning System (EWS). Despite the adversities, the programme has made substantial strides towards malaria elimination.

CONCLUSIONS

Urgent action is imperative to bolster the effectiveness of the malaria elimination programme. Key measures encompass augmenting the entomologist workforce, optimizing resource allocation, and ensuring stringent adherence to regional regulations. Addressing these concerns will enhance programme efficacy, yielding enduring public health benefits. This research substantially contributes to Indonesia's ongoing malaria elimination endeavours, furnishing actionable insights for programme enhancement. Consequently, this research holds significant importance for the malaria elimination drive.

Relative effects of climate factors and malaria control interventions on changes of parasitaemia risk in Burkina Faso from 2014 to 2017/2018

BACKGROUND

In Burkina Faso, the prevalence of malaria has decreased over the past two decades, following the scale-up of control interventions. The successful development of malaria parasites depends on several climatic factors. Intervention gains may be reversed by changes in climatic factors. In this study, we investigated the role of malaria control interventions and climatic factors in influencing changes in the risk of malaria parasitaemia.

METHODS

Bayesian logistic geostatistical models were fitted on Malaria Indicator Survey data from Burkina Faso obtained in 2014 and 2017/2018 to estimate the effects of malaria control interventions and climatic factors on the temporal changes of malaria parasite prevalence. Additionally, intervention effects were assessed at regional level, using a spatially varying coefficients model.

RESULTS

Temperature showed a statistically important negative association with the geographic distribution of parasitaemia prevalence in both surveys; however, the effects of insecticide-treated nets (ITNs) use was negative and statistically important only in 2017/2018. Overall, the estimated number of infected children under the age of 5 years decreased from 704,202 in 2014 to 290,189 in 2017/2018. The use of ITNs was related to the decline at national and regional level, but coverage with artemisinin-based combination therapy only at regional level.

CONCLUSION

Interventions contributed more than climatic factors to the observed change of parasitaemia risk in Burkina Faso during the period of 2014 to 2017/2018. Intervention effects varied in space. Longer time series analyses are warranted to determine the differential effect of a changing climate on malaria parasitaemia risk.

Assessment of malaria risk in Southeast Asia: a systematic review

BACKGROUND

Several countries in Southeast Asia are nearing malaria elimination, yet eradication remains elusive. This is largely due to the challenge of focusing elimination efforts, an area where risk prediction can play an essential supporting role. Despite its importance, there is no standard numerical method to quantify the risk of malaria infection. Thus, there is a need for a consolidated view of existing definitions of risk and factors considered in assessing risk to analyse the merits of risk prediction models. This systematic review examines studies of the risk of malaria in Southeast Asia with regard to their suitability in addressing the challenges of malaria elimination in low transmission areas.

METHODS

A search of four electronic databases over 2010-2020 retrieved 1297 articles, of which 25 met the inclusion and exclusion criteria. In each study, examined factors included the definition of the risk and indicators of malaria transmission used, the environmental and climatic factors associated with the risk, the statistical models used, the spatial and temporal granularity, and how the relationship between environment, climate, and risk is quantified.

RESULTS

This review found variation in the definition of risk used, as well as the environmental and climatic factors in the reviewed articles. GLM was widely adopted as the analysis technique relating environmental and climatic factors to malaria risk. Most of the studies were carried out in either a cross-sectional design or case-control studies, and most utilized the odds ratio to report the relationship between exposure to risk and malaria prevalence.

CONCLUSIONS

Adopting a standardized definition of malaria risk would help in comparing and sharing results, as would a clear description of the definition and method of collection of the environmental and climatic variables used. Further issues that need to be more fully addressed include detection of asymptomatic cases and considerations of human mobility. Many of the findings of this study are applicable to other low-transmission settings and could serve as a guideline for further studies of malaria in other regions.

Risk factors of malaria transmission in mining workers in Muara Enim, South Sumatra, Indonesia

Eliminating malaria by 2030 is stated as goal three in the UN's Sustainable Development Goals (SDGs). However, malaria still remains a significant public health problem. This study aims to identify the factors determining malaria transmission in artisanal or small-scale miner (ASM) communities in three villages: Tanjung Agung, Tanjung Lalang, and Penyandingan, located in the Tanjung Enim District, Muara Enim, South Sumatra, Indonesia. Researchers conducted a cross-sectional study involving 92 participants from the study area. They used a logistic regression model to investigate the risk factors related to malaria occurrence. The multivariable analysis revealed that age (Adjusted Prevalence Ratio (APR) = 7.989 with 95% CI 1.724-37.002) and mosquito breeding (APR = 7.685 with 95% CI 1.502-39.309) were risk factors for malaria. On the other hand, higher education (APR = 0.104 with 95% CI 0.027-0.403), the use of mosquito repellent (APR = 0.138 with 95% CI 0.035-0.549), and the condition of house walls (APR = 0.145 with 95% CI 0.0414-0.511) were identified as protective factors. The current study highlights age and mosquito breeding sites as risk factors for malaria. Additionally, higher education, insect repellent use, and the condition of house walls are protective factors against malaria. Therefore, reducing risk factors and increasing protective measures through effective communication, information, and education are highly recommended to eliminate malaria in mining areas.

Environmental determinants and risk behaviour in the case of indigenous malaria in Muara Enim Regency, Indonesia: A case-control design

INTRODUCTION

Malaria is a significant public health concern in Indonesia. Muara Enim Regency is one of the districts in South Sumatra with the most important number of indigenous malaria cases in the last three years (2018-2020). Therefore, this study aimed to identify determinants of indigenous malaria in the Muara Enim Regency.

METHODS

This study was designed as a case-control study. A stratified random sample in 2018, 2019, and 2020 was used at the Primary Health Centres (PHCs) areas of Tanjung Enim and Tanjung Agung. The sample included 49 cases and 49 controls. Indigenous malaria determinants were discovered using both bivariable and multivariable logistic regression models.

RESULT

The multivariable logistic regression model results show that mosquito repellent reduces malaria risk by 71% (AOR = 0.29, 95% CI: 0.11-0.64). Besides, the presence of wire mesh on ventilation reduces the risk of malaria by 76% (AOR = 0.24, 95% CI: 0.10-0.57), and the distance from mosquito breeding sites near hundred meters and fewer increases the risk of malaria by 3.88 fold (AOR = 3.88; 95% CI: 1.67-8.97).

CONCLUSIONS

Multivariable analysis revealed distance from mosquito breeding sites as a risk factor for malaria. Besides, the study shows that using insect repellent, wire netting in ventilation, eliminating mosquito breeding sites, mosquito repellent or protective clothing, and improving house conditions were protective factors for indigenous malaria. Therefore, preventive and promotional efforts are essential as the first step toward malaria elimination at the study site, including avoiding direct contact between residents and vectors near mosquito breeding sites.

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.

Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda

As found in the health studies literature, the levels of climate association between epidemiological diseases have been found to vary across regions. Therefore, it seems reasonable to allow for the possibility that relationships might vary spatially within regions. We implemented the geographically weighted random forest (GWRF) machine learning method to analyze ecological disease patterns caused by spatially non-stationary processes using a malaria incidence dataset for Rwanda. We first compared the geographically weighted regression (WGR), the global random forest (GRF), and the geographically weighted random forest (GWRF) to examine the spatial non-stationarity in the non-linear relationships between malaria incidence and their risk factors. We used the Gaussian areal kriging model to disaggregate the malaria incidence at the local administrative cell level to understand the relationships at a fine scale since the model goodness of fit was not satisfactory to explain malaria incidence due to the limited number of sample values. Our results show that in terms of the coefficients of determination and prediction accuracy, the geographical random forest model performs better than the GWR and the global random forest model. The coefficients of determination of the geographically weighted regression (R2), the global RF (R2), and the GWRF (R2) were 4.74, 0.76, and 0.79, respectively. The GWRF algorithm achieves the best result and reveals that risk factors (rainfall, land surface temperature, elevation, and air temperature) have a strong non-linear relationship with the spatial distribution of malaria incidence rates, which could have implications for supporting local initiatives for malaria elimination in Rwanda.

Climate and vector-borne diseases in Indonesia: a systematic literature review and critical appraisal of evidence

Climate is widely known as an important driver to transmit vector-borne diseases (VBD). However, evidence of the role of climate variability on VBD risk in Indonesia has not been adequately understood. We conducted a systematic literature review to collate and critically review studies on the relationship between climate variability and VBD in Indonesia. We searched articles on PubMed, Scopus, and Google Scholar databases that are published until December 2021. Studies that reported the relationship of climate and VBD, such as dengue, chikungunya, Zika, and malaria, were included. For the reporting, we followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 66 out of 284 studies were reviewed. Fifty-two (78.8%) papers investigated dengue, 13 (19.7%) papers studied malaria, one (1.5%) paper discussed chikungunya, and no (0%) paper reported on Zika. The studies were predominantly conducted in western Indonesian cities. Most studies have examined the short-term effect of climate variability on the incidence of VBD at national, sub-national, and local levels. Rainfall (n = 60/66; 90.9%), mean temperature (T_mean) (n = 50/66; 75.8%), and relative humidity (RH) (n = 50/66; 75.8%) were the common climatic factors employed in the studies. The effect of climate on the incidence of VBD was heterogenous across locations. Only a few studies have investigated the long-term effects of climate on the distribution and incidence of VBD. The paucity of high-quality epidemiological data and variation in methodology are two major issues that limit the generalizability of evidence. A unified framework is required for future research to assess the impacts of climate on VBD in Indonesia to provide reliable evidence for better policymaking.

Spatial modelling of malaria prevalence associated with geographical factors in Houet province of Burkina Faso, West Africa

Malaria is a permanent threat to health in western Burkina Faso. Research has shown that geographical variables contribute to the spatial distribution in its transmission. The objective of this study is to assess the relationship between malaria prevalence and potential explanatory geographical variables in the Houet province in Burkina Faso. Statistics on malaria prevalence registered by health centres in the Houet province in 2017 and potential geographical variables identified through a literature review were collected. An Ordinary Least Squares (OLS) regression was used to identify key geographical variables and to measure their association with malaria while the Getis Ord Gi* index was used to locate malaria hotspots. The results showed that average annual temperature, vegetation density, percentage of clay in the soil, total annual rainfall and distance to the nearest waterbody are the main variables associated with malaria prevalence. These variables account for two-thirds of the spatial variability of malaria prevalence observed in Houet province. The intensity and direction of the relationship between malaria prevalence and geographical factors vary according to the variable. Hence, only vegetation density is positively correlated with malaria prevalence. Average temperature, for soil clay content, annual rainfall and for distance to the nearest water body are negatively correlated with the disease prevalence. These results show that even in an endemic area, malaria prevalence has significant spatial variation. The results could contribute to the choice of intervention sites, as this choice is crucial for reducing the malaria burden.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10708-022-10692-7.

Big Geospatial Data or Geospatial Big Data? A Systematic Narrative Review on the Use of Spatial Data Infrastructures for Big Geospatial Sensing Data in Public Health

Background: Often combined with other traditional and non-traditional types of data, geospatial sensing data have a crucial role in public health studies. We conducted a systematic narrative review to broaden our understanding of the usage of big geospatial sensing, ancillary data, and related spatial data infrastructures in public health studies. Methods: English-written, original research articles published during the last ten years were examined using three leading bibliographic databases (i.e., PubMed, Scopus, and Web of Science) in April 2022. Study quality was assessed by following well-established practices in the literature. Results: A total of thirty-two articles were identified through the literature search. We observed the included studies used various data-driven approaches to make better use of geospatial big data focusing on a range of health and health-related topics. We found the terms ‘big’ geospatial data and geospatial ‘big data’ have been inconsistently used in the existing geospatial sensing studies focusing on public health. We also learned that the existing research made good use of spatial data infrastructures (SDIs) for geospatial sensing data but did not fully use health SDIs for research. Conclusions: This study reiterates the importance of interdisciplinary collaboration as a prerequisite to fully taking advantage of geospatial big data for future public health studies.

Spatial differentiation and determinants of COVID-19 in Indonesia

BACKGROUND

The spread of the coronavirus disease 2019 (COVID-19) has increasingly agonized daily lives worldwide. As an archipelagic country, Indonesia has various physical and social environments, which implies that each region has a different response to the pandemic. This study aims to analyze the spatial differentiation of COVID-19 in Indonesia and its interactions with socioenvironmental factors.

METHODS

The socioenvironmental factors include seven variables, namely, the internet development index, literacy index, average temperature, urban index, poverty rate, population density (PD) and commuter worker (CW) rate. The multiple linear regression (MLR) and geographically weighted regression (GWR) models are used to analyze the impact of the socioenvironmental factors on COVID-19 cases. COVID-19 data is obtained from the Indonesian Ministry of Health until November 30th 2020.

RESULTS

Results show that the COVID-19 cases in Indonesia are concentrated in Java, which is a densely populated area with high urbanization and industrialization. The other provinces with numerous confirmed COVID-19 cases include South Sulawesi, Bali, and North Sumatra. This study shows that the socioenvironmental factors, simultaneously, influence the increasing of confirmed COVID-19 cases in the 34 provinces of Indonesia. Spatial interactions between the variables in the GWR model are relatively better than those between the variables in the MLR model. The highest spatial tendency is observed outside Java, such as in East Nusa Tenggara, West Nusa Tenggara, and Bali.

CONCLUSION

Priority for mitigation and outbreak management should be high in areas with high PD, urbanized spaces, and CW.

Anopheline Diversity in Indonesia: An Evaluation of Animal-Baited Sampling Techniques

Indonesia has rich Anopheline (Diptera: Culicidae) mosquito species living in various types of ecosystems. The study was conducted to profile and compare Anopheles diversity, equitability, and dominance in various ecosystems using different animal-based sampling techniques. The present study analyzed a subset of data collected from a nation-wide vector and animal reservoirs survey in 2016. Analyses were restricted to three ecosystem types (forest, nonforest, and coastal areas) in Java and Sumatera Islands. A total of 5,477 Anopheles were collected by using animal-baited (n = 1,909) and animal-baited trap nets (n = 1,978), consisting of 23 Anopheline species. Overall, Anopheles vagus was the most abundant species, followed by An. subpictus and An. barbirostris. Among the three ecosystems, the forest had a higher diversity index (H' = 1.98), but each ecosystem has its specific predominant species. Compared with the animal-baited method, the Anopheles abundance collected by animal-baited trap nets was two-fold higher. Ecosystem, elevation, and sampling methods were associated with the abundance of female Anopheles (P-value < 0.001). Our findings revealed that Anopheles were found in a different ecosystem, indicating the potential of malaria transmission. This suggests that improved malaria vector surveillance is essential in all types of ecosystem. Furthermore, the study suggested that animal-baited trap nets could be used as the standard method of outdoor resting sampling in Indonesia in addition to the traditional human landing collection approach.

The Increasing Surface Ozone and Tropospheric Ozone in Antarctica and Their Possible Drivers

A comprehensive analysis of the temporal evolution of tropospheric ozone in Antarctica using more than 25 years of surface ozone and ozonesonde measurements reveals significant changes in tropospheric ozone there. It shows a positive trend in ozone at the surface and lower and mid-troposphere, but a negative trend in the upper troposphere. We also find significant links between different climate modes and tropospheric ozone in Antarctica and observe that changes in residual overturning circulation, the strength of the polar vortex, and stratosphere-troposphere exchange make noticeable variability in tropospheric ozone. Therefore, this study alerts of increasing ozone concentration in Antarctica, which would have a profound impact on the future climate of the region as tropospheric ozone has warming feedback to the Earth's climate.

Rapid diagnostic testing as an indicator of malaria prevalence in Rorya District, Tanzania

BACKGROUND

Rapid Diagnostic Testing (RDT), a point-of-care, qualitative test for Plasmodium antigen, has been a catalyst in the diagnosis of patients in malaria-endemic regions. While blood-smear microscopy remains the gold standard, RDT allows for swift diagnosis in resource-poor settings. Our study sought to utilize RDT to quantify local malaria prevalence in the Rorya district of Tanzania.

MATERIALS AND METHODS

Two field clinics were established and 1,032 patients were screened. Those that described malaria symptoms were tested via RDT. The percentage of positive tests was compared to national data from the World Health Organization's 2019 World Malaria report and the President's Malaria Initiative Report for Tanzania. Intake data (sex, age, heart rate (HR), and temperature) were compared between the malaria-positive and malaria-negative groups.

RESULTS

772 patients received RDT of whom 487 tested positive. There was a statistically significant difference in the percentage of positive patients between the two sites (52.0% vs 38.2%). Sixty percent of malaria-positives were female and the median age of this group was 10 yrs (range 5-15 yrs). Intake data showed a notable difference in median heart rates between malaria-positive and malaria-negative persons, 84.0 (72-100) and 72.0 (74-84) beats per minute (bpm), respectively.

CONCLUSIONS

The prevalence of malaria in Rorya was significantly higher than the reported Tanzanian average. Additionally, children were at a statistically higher risk of contracting malaria. Our data indicates that RDT offers enhanced insight into the local malarial burden that may be valuable to (governmental) health providers for the disbursement of resources in malaria-endemic regions.

Spatial analysis of malaria in Kotabaru, South Kalimantan, Indonesia: an evaluation to guide elimination strategies

BACKGROUND

Malaria remains a significant public health concern in Indonesia. Knowledge about spatial patterns of the residual malaria hotspots is critical to help design elimination strategies in Kotabaru district, South Kalimantan, Indonesia.

METHODS

Laboratory-confirmed malaria cases from 2012 to 2016 were analysed to examine the trend in malaria cases. Decomposition analysis was performed to assess seasonality. Annual spatial clustering of the incidence and hotspots were identified by Moran's I and the local indicator for spatial association, respectively.

RESULTS

The annual parasite incidence of malaria was significantly reduced by 87% from 2012 to 2016. Plasmodium vivax infections were significantly much more prevalent over time, followed by Plasmodium falciparum infections (p<0.001). The monthly seasonality of P. vivax and P. falciparum was distinct. High incidence was spatially clustered identified in the north, west and parts of south Kotabaru. Two persistent and four re-emerging high-risk clusters were identified during the period. Despite the significant reduction in the incidence of malaria, the residual high-risk villages remained clustered in the northern part of Kotabaru.

CONCLUSIONS

A spatially explicit decision support system is needed to support surveillance and control programs in the identified high-risk areas to succeed in the elimination goal of 2030.

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.

Estimating the local spatio-temporal distribution of malaria from routine health information systems in areas of low health care access and reporting

BACKGROUND

Reliable surveillance systems are essential for identifying disease outbreaks and allocating resources to ensure universal access to diagnostics and treatment for endemic diseases. Yet, most countries with high disease burdens rely entirely on facility-based passive surveillance systems, which miss the vast majority of cases in rural settings with low access to health care. This is especially true for malaria, for which the World Health Organization estimates that routine surveillance detects only 14% of global cases. The goal of this study was to develop a novel method to obtain accurate estimates of disease spatio-temporal incidence at very local scales from routine passive surveillance, less biased by populations' financial and geographic access to care.

METHODS

We use a geographically explicit dataset with residences of the 73,022 malaria cases confirmed at health centers in the Ifanadiana District in Madagascar from 2014 to 2017. Malaria incidence was adjusted to account for underreporting due to stock-outs of rapid diagnostic tests and variable access to healthcare. A benchmark multiplier was combined with a health care utilization index obtained from statistical models of non-malaria patients. Variations to the multiplier and several strategies for pooling neighboring communities together were explored to allow for fine-tuning of the final estimates. Separate analyses were carried out for individuals of all ages and for children under five. Cross-validation criteria were developed based on overall incidence, trends in financial and geographical access to health care, and consistency with geographic distribution in a district-representative cohort. The most plausible sets of estimates were then identified based on these criteria.

RESULTS

Passive surveillance was estimated to have missed about 4 in every 5 malaria cases among all individuals and 2 out of every 3 cases among children under five. Adjusted malaria estimates were less biased by differences in populations' financial and geographic access to care. Average adjusted monthly malaria incidence was nearly four times higher during the high transmission season than during the low transmission season. By gathering patient-level data and removing systematic biases in the dataset, the spatial resolution of passive malaria surveillance was improved over ten-fold. Geographic distribution in the adjusted dataset revealed high transmission clusters in low elevation areas in the northeast and southeast of the district that were stable across seasons and transmission years.

CONCLUSIONS

Understanding local disease dynamics from routine passive surveillance data can be a key step towards achieving universal access to diagnostics and treatment. Methods presented here could be scaled-up thanks to the increasing availability of e-health disease surveillance platforms for malaria and other diseases across the developing world.

Disparities in Risks of Malaria Associated with Climatic Variability among Women, Children and Elderly in the Chittagong Hill Tracts of Bangladesh

Malaria occurrence in the Chittagong Hill Tracts in Bangladesh varies by season and year, but this pattern is not well characterized. The role of environmental conditions on the occurrence of this vector-borne parasitic disease in the region is not fully understood. We extracted information on malaria patients recorded in the Upazila (sub-district) Health Complex patient registers of Rajasthali in Rangamati district of Bangladesh from February 2000 to November 2009. Weather data for the study area and period were obtained from the Bangladesh Meteorological Department. Non-linear and delayed effects of meteorological drivers, including temperature, relative humidity, and rainfall on the incidence of malaria, were investigated. We observed significant positive association between temperature and rainfall and malaria occurrence, revealing two peaks at 19 °C (logarithms of relative risks (logRR) = 4.3, 95% CI: 1.1-7.5) and 24.5 °C (logRR = 4.7, 95% CI: 1.8-7.6) for temperature and at 86 mm (logRR = 19.5, 95% CI: 11.7-27.3) and 284 mm (logRR = 17.6, 95% CI: 9.9-25.2) for rainfall. In sub-group analysis, women were at a much higher risk of developing malaria at increased temperatures. People over 50 years and children under 15 years were more susceptible to malaria at increased rainfall. The observed associations have policy implications. Further research is needed to expand these findings and direct resources to the vulnerable populations for malaria prevention and control in the Chittagong Hill Tracts of Bangladesh and the region with similar settings.

Spatial and spatio-temporal analysis of malaria cases in Zimbabwe

Background

Although effective treatment for malaria is now available, approximately half of the global population remain at risk of the disease particularly in developing countries. To design effective malaria control strategies there is need to understand the pattern of malaria heterogeneity in an area. Therefore, the main objective of this study was to explore the spatial and spatio-temporal pattern of malaria cases in Zimbabwe based on malaria data aggregated at district level from 2011 to 2016.

Methods

Geographical information system (GIS) and spatial scan statistic were applied on passive malaria data collected from health facilities and aggregated at district level to detect existence of spatial clusters. The global Moran’s I test was used to infer the presence of spatial autocorrelation while the purely spatial retrospective analyses were performed to detect the spatial clusters of malaria cases with high rates based on the discrete Poisson model. Furthermore, space-time clusters with high rates were detected through the retrospective space-time analysis based on the discrete Poisson model.

Results

Results showed that there is significant positive spatial autocorrelation in malaria cases in the study area. In addition, malaria exhibits spatial heterogeneity as evidenced by the existence of statistically significant (P < 0.05) spatial and space-time clusters of malaria in specific geographic regions. The detected primary clusters persisted in the eastern region of the study area over the six year study period while the temporal pattern of malaria reflected the seasonality of the disease where clusters were detected within particular months of the year.

Conclusions

Geographic regions characterised by clusters of high rates were identified as malaria high risk areas. The results of this study could be useful in prioritizing resource allocation in high-risk areas for malaria control and elimination particularly in resource limited settings such as Zimbabwe. The results of this study are also useful to guide further investigation into the possible determinants of persistence of high clusters of malaria cases in particular geographic regions which is useful in reducing malaria burden in such areas.

Potential for a web-based management information system to improve malaria control: An exploratory study in the Lahat District, South Sumatra Province, Indonesia

Background

A web-based malaria reporting information system (MRIS) has the potential to improve malaria reporting and management. The aim of this study was to evaluate the existing manual paper-based MRIS and to provide a way to overcome the obstacles by developing a web-based MRIS in Indonesia.

Methods

An exploratory study was conducted in 2012 in Lahat District, South Sumatra Province of Indonesia. We evaluated the current reporting system and identified the potential benefits of using a web-based MRIS by in-depth interviews on selected key informants. Feasibility study was then conducted to develop a prototype system. A web-based MRIS was developed, integrated and synchronized, with suitability ranging from Primary Healthcare Centres (PHCs) to the Lahat District Health Office.

Results

The paper-based reporting system was sub-optimal due to a lack of transportation, communication, and human capacity. We developed a web-based MRIS to replace the current one. Although the web-based system has the potential to improve the malaria reporting information system, there were some barriers to its implementation, including lack of skilled operators, computer availability and lack of internet access. Recommended ways to overcome the obstacles are by training operators, making the application in an offline mode and able to be operated by mobile phone text messaging for malaria reporting.

Conclusion

The web-based MRIS has the potential to be implemented as an enhanced malaria reporting information system and investment in the system to support timely management responses is essential for malaria elimination. The developed application can be cloned to other areas that have similar characteristics and MRIS with a built-in web base to aid its application in the 5G future.

Improving the efficiency of reactive case detection for malaria elimination in southern Zambia: a cross-sectional study

Background

Reactive case detection (RCD) seeks to enhance malaria surveillance and control by identifying and treating parasitaemic individuals residing near index cases. In Zambia, this strategy starts with passive detection of symptomatic incident malaria cases at local health facilities or by community health workers, with subsequent home visits to screen-and-treat residents in the index case and neighbouring (secondary) households within a 140-m radius using rapid diagnostic tests (RDTs). However, a small circular radius may not be the most efficient strategy to identify parasitaemic individuals in low-endemic areas with hotspots of malaria transmission. To evaluate if RCD efficiency could be improved by increasing the probability of identifying parasitaemic residents, environmental risk factors and a larger screening radius (250 m) were assessed in a region of low malaria endemicity.

Methods

Between January 12, 2015 and July 26, 2017, 4170 individuals residing in 158 index and 531 secondary households were enrolled and completed a baseline questionnaire in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia. Plasmodium falciparum prevalence was measured using PfHRP2 RDTs and quantitative PCR (qPCR). A Quickbird™ high-resolution satellite image of the catchment area was used to create environmental risk factors in ArcGIS, and generalized estimating equations were used to evaluate associations between risk factors and secondary households with parasitaemic individuals.

Results

The parasite prevalence in secondary (non-index case) households was 0.7% by RDT and 1.8% by qPCR. Overall, 8.5% (n = 45) of secondary households had at least one resident with parasitaemia by qPCR or RDT. The risk of a secondary household having a parasitaemic resident was significantly increased in proximity to higher order streams and marginally with increasing distance from index households. The adjusted OR for proximity to third- and fifth-order streams were 2.97 (95% CI 1.04–8.42) and 2.30 (95% CI 1.04–5.09), respectively, and that for distance to index households for each 50 m was 1.24 (95% CI 0.98–1.58).

Conclusion

Applying proximity to streams as a screening tool, 16% (n = 3) more malaria-positive secondary households were identified compared to using a 140-m circular screening radius. This analysis highlights the potential use of environmental risk factors as a screening strategy to increase RCD efficiency.

The changing modes of human immunodeficiency virus transmission and spatial variations among women in a minority prefecture in southwest China: An exploratory study

Liangshan Yi Autonomous Prefecture in Southwest China has a high human immunodeficiency virus (HIV) prevalence rate. This study examined the changing modes of HIV transmission among women with new HIV infections and explored the spatial heterogeneities in the factors associated with heterosexual transmission in this minority region.The data consisting of women with new HIV infections from 2011 to 2014 were collected from multiple sources. New infections were identified by BED capture enzyme immunoassay. The Bayesian hierarchical model was used to estimate the proportion of women with new HIV infections via heterosexual transmission across all townships in the Prefecture. A geographically weighted regression (GWR) model was utilized to investigate spatial variations in the sociodemographic characteristics associated with the changing modes of HIV transmission.An analytical sample of 927 women with new HIV infections was constructed and utilized to investigate the changing mode of HIV transmission. The rate of heterosexual transmission among women with new HIV infections in 2011 was below 20%. However, by 2014 this rate dramatically increased to nearly 80%. Among sociodemographic characteristics, GWR results revealed significant ethnic differences in heterosexual HIV transmission between Yi women and women in other ethnic groups, with Yi women demonstrating a lower risk of infection through heterosexual transmission. However, such ethnic differences were observed only in 30% of the townships in the Prefecture. Moreover, having a primary education decreased the odds of heterosexual transmission, which was observed in about 56% of the townships. Also, being involved in occupations other than agriculture or animal husbandry and being single or married decreased the odds of HIV infection through heterosexual contact among women, which did not significantly vary across the Prefecture.Heterosexual transmission was the predominant mode of HIV transmission among women in the Prefecture, and this transformation was clearly marked by a fast-growing trend and a spatial diffusion pattern. Spatial variations also existed in sociodemographic factors that were associated with the changing modes of HIV transmission.

The Role of Ecological Linkage Mechanisms in Plasmodium knowlesi Transmission and Spread

Defining the linkages between landscape change, disease ecology and human health is essential to explain and predict the emergence of Plasmodium knowlesi malaria, a zoonotic parasite residing in Southeast Asian macaques, and transmitted by species of Anopheles mosquitos. Changing patterns of land use throughout Southeast Asia, particularly deforestation, are suggested to be the primary drivers behind the recent spread of this zoonotic parasite in humans. Local ecological changes at the landscape scale appear to be increasing the risk of disease in humans by altering the dynamics of transmission between the parasite and its primary hosts. This paper will focus on the emergence of P. knowlesi in humans in Malaysian Borneo and the ecological linkage mechanisms suggested to be playing an important role.

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.

Individual and contextual factors predicting self-reported malaria among adults in eastern Indonesia: findings from Indonesian community-based survey

BACKGROUND

Malaria is still an important parasitic infectious disease that affecting poor and vulnerable communities in many developing countries, including Indonesia. During the period of 2010-2017, there have been approximately 2.2 million confirmed malaria cases reported across Indonesia. This study aimed to identify individual, household and village-level factors associated with self-reported malaria among adults more than 15 years of age in Maluku, West Papua and Papua province.

METHODS

This study analysed a subset of the data from nationally representative population-based Indonesian National Basic Health Research (Riset Kesehatan Dasar) (N = 1,027,763 in 294,959 households in 33 provinces) in 2013. Total of 41,079 individuals (20,326 males and 20,753 females) aged ≥ 15 years in 19,269 households in Maluku, West Papua and Papua provinces were included. Participants were interviewed if they ever had been diagnosed and laboratory confirmed of having malaria by physician in the past 12 months. A mixed effects multilevel logistic regression models were developed to assess the associations between socio-demographical variables at individual, household and village level and self-reported malaria.

RESULTS

Individuals aged ≥ 15 years in 701 villages in Maluku (n = 11,919), West Papua (n = 8003) and Papua (n = 21,157) were analysed. In all provinces, gender distribution was equally-represented. The prevalence of self-reported malaria was 4.1% (Maluku), 12.4% (West Papua) and 18.8% (Papua). At the individual level, primary industry workers (OR 1.29, 95% CI 1.15-1.46 [Maluku]; OR 1.17, 95% CI 1.09-1.25 [Papua]) and having higher education were associated with self-reporting malaria (OR 0.67, 95% CI 0.53-0.83 [Maluku]; OR 1.27, 95% CI 1.15-1.40 [Papua]). Household level factors include having bed net and better off wealth index were associated with increased self-reporting malaria among West Papua (OR 1.21; 95% CI 1.09-1.34 and OR 1.38; 95% CI 1.17-1.65, respectively) and Papuan (OR 1.12; 95% CI 1.02-1.23 and OR 1.33; 95% CI 1.11-1.57, respectively) adults. Increased odds of self-reporting malaria was associated with time required to reach healthcare facility (OR 1.30, 95% CI 1.01-1.67 [Maluku]). Contextual village-level characteristics such as living in rural (OR 1.31, 95% CI 1.12-1.54 [Maluku]; OR 1.56, 95% CI 1.17-2.07 [West Papua]), higher community education level (OR 1.28, 95% CI 1.02-1.63 [West Papua]; OR 1.45, 95% CI 1.23-1.72 [Papua]), higher community bed net ownerships (OR 0.59 95% CI 0.45-0.77 [West Papua]) were associated with self-reported malaria.

CONCLUSIONS

Factors associated with self-reported malaria were varied between provinces suggesting locally-specific determinants were exist at individual, household and community-level. This study highlights the need for specific interventions by taking into consideration the contextual factors within the region and involving multi-sectoral collaboration between health authorities and related stakeholders (e.g., bureau of education, bureau of public works and infrastructure) to improve designs in planning and intervention strategies to succesfully eliminate malaria in Maluku and Papua.