Social determinants of malaria in an endemic area of Indonesia

Exploring mosquito abundance and Plasmodium infection through nested-PCR: implications for disease surveillance and control

The Plasmodium is responsible for malaria which poses a major health threat, globally. This study is based on the estimation of the relative abundance of mosquitoes, and finding out the correlations of meteorological parameters (temperature, humidity and rainfall) with the abundance of mosquitoes. In addition, this study also focused on the use of nested PCR (species-specific nucleotide sequences of 18S rRNA genes) to explore the Plasmodium spp. in female Anopheles. In the current study, the percentage relative abundance of Culex mosquitoes was 57.65% and Anopheles 42.34% among the study areas. In addition, the highest number of mosquitoes was found in March in district Mandi Bahauddin at 21 °C (Tmax = 27, Tmin = 15) average temperature, 69% average relative humidity and 131 mm rainfall, and these climatic factors were found to affect the abundance of the mosquitoes, directly or indirectly. Molecular analysis showed that overall, 41.3% of the female Anopheles pools were positive for genus Plasmodium. Among species, the prevalence of Plasmodium (P.) vivax (78.1%) was significantly higher than P. falciparum (21.9%). This study will be helpful in the estimation of future risk of mosquito-borne diseases along with population dynamic of mosquitoes to enhance the effectiveness of vector surveillance and control programs.

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach

Malaria ranks high among prevalent and ravaging infectious diseases in sub-Saharan Africa (SSA). The negative impacts, disease burden, and risk are higher among children and pregnant women as part of the most vulnerable groups to malaria in Nigeria. However, the burden of malaria is not even in space and time. This study explores the spatial variability of malaria prevalence among children under five years (U5) in medium-sized rapidly growing city of Akure, Nigeria using model-based geostatistical modeling (MBG) technique to predict U5 malaria burden at a 100 × 100 m grid, while the parameter estimation was done using Monte Carlo maximum likelihood method. The non-spatial logistic regression model shows that U5 malaria prevalence is significantly influenced by the usage of insecticide-treated nets-ITNs, window protection, and water source. Furthermore, the MBG model shows predicted U5 malaria prevalence in Akure is greater than 35% at certain locations while we were able to ascertain places with U5 prevalence > 10% (i.e. hotspots) using exceedance probability modelling which is a vital tool for policy development. The map provides place-based evidence on the spatial variation of U5 malaria in Akure, and direction on where intensified interventions are crucial for the reduction of U5 malaria burden and improvement of urban health in Akure, Nigeria.

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.

Grasp of dihydroartemisinin resistance in Indonesia: Focused on genetic polymorphisms and new antimalarial

The eastern region of Indonesia is endemic to malaria, a tropical parasitic infection that causes significant mortality. The Sustainable Development Goals (SDGs) encompass the global commitment to prevent and eliminate malaria by the end of 2030. Nevertheless, the biggest issue lies in the antimalarial drug resistance in Indonesia. Genetic polymorphism has been a considerable factor in the mechanism of antimalarial drug resistance of which could lead to inadequate activity of antimalarial drugs to undertake Plasmodium infection by several molecular mechanisms. Hence, first-line therapy for malaria in Indonesia such as dihydroartemisinin, piperaquine, and primaquine, becomes ineffective. However, the resistance is unavoidable. This review aims to summarize the genetic polymorphism possible mechanisms contributing to antimalarial resistance in the Indonesian population and to discuss the potential new antimalarial drug candidates.

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.

Malaria Preventive Practices among People Residing in Different Malaria-Endemic Settings in a Township of Myanmar: A Mixed-Methods Study

Different villages in a township or an area exhibit different malaria endemicities. This study aimed to investigate malaria preventive practices among people residing in different villages with stratified malaria endemicity in a township in Myanmar. Quantitative data were collected using standardized questionnaires by conducting face-to-face interviews, and qualitative data were obtained through in-depth interviews using a guideline. Quantitative data were analyzed using descriptive statistics and logistic regression models, whereas thematic analysis was used to visualize qualitative data. A total of 360 respondents with similar characteristics participated in the quantitative study. Knowledge regarding malaria and the availability of health information exhibited insignificant differences. Malaria preventive practices were considerably poor among people from moderate- and high-endemic villages (p < 0.05). Adult male farmers or gold miners with low annual family incomes reported poor preventive practices in both moderate- and high-endemic groups. People could not practice some malaria preventive measures because of a lack of resources, e.g., a lack of mosquito repellents. To eliminate the disparities of preventive practices in different malaria-endemic settings, heath-awareness-raising activities should be increased, especially in moderate- and high-endemic villages.

Multilevel logistic regression modelling to quantify variation in malaria prevalence in Ethiopia

Background

Ethiopia has low malaria prevalence compared to most other malaria-endemic countries in Africa. However, malaria is still a major public health problem in the country. The binary logistic regression model has been widely used to analyse malaria indicator survey (MIS) data. However, most MIS have a hierarchical structure which may result in dependent data. Since this model assumes that conditional on the covariates the malaria statuses of individuals are independent, it ignores potential intra-cluster correlation among observations within a cluster and may generate biased analysis results and conclusions. Therefore, the aim of this study was to quantify the variation in the prevalence of malaria between sample enumeration areas (SEAs) or clusters, the effects of cluster characteristics on the prevalence of malaria using the intra-class correlation coefficient as well as to identify significant factors that affect the prevalence of malaria using the multilevel logistic regression modelling in three major regions of Ethiopia, namely Amhara, Oromia and Southern Nations, Nationalities and Peoples’ (SNNP).

Methods

Dataset for three regional states extracted from the 2011 Ethiopian National Malaria Indicator Surveys (EMIS) national representative samples was used in this study. It contains 9272 sample individuals selected from these regions. Various multilevel models with random sample SEA effects were applied taking into account the survey design weights. These weights are scaled to address unequal probabilities of selection within clusters. The spatial clustering of malaria prevalence was assessed applying Getis-Ord statistic to best linear unbiased prediction values of model random effects.

Results

About 53.82 and 28.72 per cents of the sampled households in the study regions had no mosquito net and sprayed at least once within the last 12 months, respectively. The results of this study indicate that age, gender, household had mosquito nets, the dwelling has windows, source of drinking water, the two SEA-level variables, i.e. region and median altitude, were significantly related to the prevalence of malaria. After adjusting for these seven variables, about 45% of the residual variation in the prevalence of malaria in the study regions was due to systematic differences between SEAs, while the remaining 55% was due to unmeasured differences between persons or households. The estimated MOR, i.e. the unexplained SEA heterogeneity, was 4.784. This result suggests that there is high variation between SEAs in the prevalence of malaria. In addition, the 80% interval odds ratios (IORs) related to SEA-level variables contain one suggesting that the SEA variability is large in comparison with the effect of each of the variable.

Conclusions

The multilevel logistic regression with random effects model used in this paper identified five individual / household and two SEA-level risk factors of malaria infection. Therefore, the public health policy makers should pay attentions to those significant factors, such as improving the availability of pure drinking water. Further, the findings of spatial clustering provide information to health policymakers to plan geographically targeted interventions to control malaria transmission.

Factors influencing severity of recurrent malaria in a conflict-affected state of South Sudan: an unmatched case-control study

Background

The burden of malaria remains the highest in sub-Saharan Africa and South Sudan is not an exception. The country has borne the brunt of years of chronic warfare and remains endemic of malaria, with increasing mortality and morbidity. Limited data still exists on factors influencing the recurrence of severe malaria, especially in emergency contexts such as South Sudan, affected by various conflicts and humanitarian situations. This study therefore aimed to investigate factors influencing severity of occurrence malaria in selected primary healthcare centres in South Sudan. This would assist and guide in malaria prevention, treatment, and eradication efforts.

Methods

We conducted an unmatched case-control study using routinely collected clinic data for individuals aged 1 year and above who received a diagnosis of severe malaria at 3 primary healthcare centres (PHCC); Malual Bab PHCC, Matangai PHCC and Malek PHCC between September 15, 2019 to December 15, 2019 in South Sudan. Patient characteristics were analyzed using simple descriptive statistics. Inferential statistics were also conducted to identify the associated factors influencing recurrence of severe malaria. All analyses were conducted using R Version 3.6.2.

Results

A total of 289 recurrent malaria cases were included in this study. More than half of the participants were female. Overall, the prevalence of severe recurrent malaria was 66.1% (191) while 74.4% (215) did not complete malaria treatment. Among those who did not complete malaria treatment, 76.7% (165) had severe recurrent malaria, while among those who completed malaria treatment 35.1% (26) had severe recurrent malaria (p < 0.001). There is a significant association between marital status (OR 0.33, 95% CI 0.19–0.56, p < 0.001), employment status (OR 0.35, 95% CI 0.14–0.87, p = 0.024), the use of preventive measures (OR 3.82, 95% CI 1.81–8.43, p < 0.001) and nutrition status (OR 0.22, 95% CI 0.13–0.37, p < 0.001). When adjusted for employment, marital status, nutritional and prevention measures in turns using Mantel–Haenszel test of association, this effect remained statistically significant.

Conclusions

Our study showed that there is a high prevalence of severe recurrent malaria in South Sudan and that a significant relationship exists between severe recurrent malaria and antimalarial treatment dosage completion influenced by certain personal and social factors such as marital status, employment status, the use of preventive measures and nutrition status. Findings from our study would be useful for effective response to control and prevent malaria in endemic areas of South Sudan.

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.

Malaria diagnostic methods with the elimination goal in view

Malaria control measures have been in use for years but have not completely curbed the spread of infection. Ultimately, global elimination is the goal. A major playmaker in the various approaches to reaching the goal is the issue of proper diagnosis. Various diagnostic techniques were adopted in different regions and geographical locations over the decades, and these have invariably produced diverse outcomes. In this review, we looked at the various approaches used in malaria diagnostics with a focus on methods favorably used during pre-elimination and elimination phases as well as in endemic regions. Microscopy, rapid diagnostic testing (RDT), loop-mediated isothermal amplification (LAMP), and polymerase chain reaction (PCR) are common methods applied depending on prevailing factors, each with its strengths and limitations. As the drive toward the elimination goal intensifies, the search for ideal, simple, fast, and reliable point-of-care diagnostic tools is needed more than ever before to be used in conjunction with a functional surveillance system supported by the ideal vaccine.

Sub-national disparities in accessing anti-malarial drug treatment in eastern Indonesia

BACKGROUND

Poor access to health care providers was among the contributing factors to less prompt and ineffective malaria treatment. This limitation could cause severe diseases in remote areas. This study examined the sub-national disparities and predictors in accessing anti-malarial drug treatment among adults in Eastern Indonesia.

METHODS

The study analyzed a subset of the 2018 National Basic Health Survey conducted in all 34 provinces in Indonesia. We extracted socio-demographic data of 4655 adult respondents diagnosed with malaria in the past 12 months in five provinces in Eastern Indonesia. The association between socio-demographic factors and the access to anti-malarial drug treatment was assessed using logistic regression.

RESULTS

Over 20% of respondents diagnosed with malaria within last 12 months admitted that they did not receive anti-malarial drug treatment (range 12-29.9%). The proportion of untreated cases was 12.0% in East Nusa Tenggara, 29.9% in Maluku, 23.1% in North Maluku, 12.7% in West Papua, and 15.6% in Papua. The likelihood of receiving anti-malarial drug treatment was statistically lower in Maluku (adjusted OR = 0.258; 95% CI 0.161-0.143) and North Maluku (adjusted OR = 0.473; 95% CI 0.266-0.840) than those in Eastern Nusa Tenggara (reference). Urban respondents were less likely to receive malaria treatment than rural (adjusted OR = 0.545; 95% CI 0.431-0.689).

CONCLUSIONS

This study found that there were sub-national disparities in accessing anti-malarial drug treatment in Eastern Indonesia, with a high proportion of untreated malaria cases across the areas. Findings from this study could be used as baseline information to improve access to anti-malarial drug treatment and better target malaria intervention in Eastern Indonesia.

Epidemiology of Malaria in East Nusa Tenggara Province in Indonesia: Protocol for a Cross-sectional Study

Background

Malaria is a global pandemic that results in approximately 228 million cases globally; 3.5% of these cases are in Southeast Asian countries, including Indonesia. Following the World Health Organization (WHO) initiative, Indonesia is in the process of achieving malaria-free zone status by 2030. However, the eastern part of Indonesia, including the East Nusa Tenggara Province (ENTP), still has a disproportionately high rate of malaria.

Objective

The aims of this cross-sectional study are to determine the awareness and knowledge, attitude, and practice toward various aspects of malaria among rural adults and their associated factors, including sociodemographic factors and ethnicities; assess the gap between coverage of, access to, and use of long-lasting insecticide-treated nets (LLINs) among the households; estimate the prevalence of and factors associated with malaria in rural adults; and develop a risk prediction model for malaria.

Methods

A multistage cluster sampling procedure with a systematic random sampling procedure at cluster level 4 was applied to recruit 1503 adults aged 18 years or older from the ENTP. Each participant participated in a face-to-face interview to assess their awareness and knowledge, attitude, and practice toward aspects of malaria, practices of sleeping under LLINs, and history of malaria. Information on sociodemographic, environmental, and lifestyle factors was also documented. The proportion of knowledge, attitude, and practice toward aspects of malaria and their variations across different sociodemographic and ethnic groups will be analyzed using descriptive statistics and chi-square tests. Coverage and access to LLINs will be evaluated based on the WHO recommendations. Malaria risk factors will be analyzed using logistic regression. Multilevel logistic regression will be applied to estimate the risk score for malaria.

Results

Of the total participants, 99.46% (1495/1503) of rural adults from 49 villages in the ENTP participated in a face-to-face interview from October to December 2019. The study results are expected to be published in peer-reviewed journals.

Conclusions

The best malaria risk prediction model will be developed in this study. In this protocol, we developed a methodology to provide new evidence to guide health policy in supporting the ENTP government’s expectation to achieve the malaria-free rating by 2030.

International Registered Report Identifier (IRRID)

DERR1-10.2196/23545

Anthropogenic landscape decreases mosquito biodiversity and drives malaria vector proliferation in the Amazon rainforest

Inter-relationships among mosquito vectors, Plasmodium parasites, human ecology, and biotic and abiotic factors, drive malaria risk. Specifically, rural landscapes shaped by human activities have a great potential to increase the abundance of malaria vectors, putting many vulnerable people at risk. Understanding at which point the abundance of vectors increases in the landscape can help to design policies and interventions for effective and sustainable control. Using a dataset of adult female mosquitoes collected at 79 sites in malaria endemic areas in the Brazilian Amazon, this study aimed to (1) verify the association among forest cover percentage (PLAND), forest edge density (ED), and variation in mosquito diversity; and to (2) test the hypothesis of an association between landscape structure (i.e., PLAND and ED) and Nyssorhynchus darlingi (Root) dominance. Mosquito collections were performed employing human landing catch (HLC) (peridomestic habitat) and Shannon trap combined with HLC (forest fringe habitat). Nyssorhynchus darlingi abundance was used as the response variable in a generalized linear mixed model, and the Shannon diversity index (H') of the Culicidae community, PLAND, and the distance house-water drainage were used as predictors. Three ED categories were also used as random effects. A path analysis was used to understand comparative strengths of direct and indirect relationships among Amazon vegetation classes, Culicidae community, and Ny. darlingi abundance. Our results demonstrate that Ny. darlingi is negatively affected by H´ and PLAND of peridomestic habitat, and that increasing these variables (one-unit value at β0 = 768) leads to a decrease of 226 (P < 0.001) and 533 (P = 0.003) individuals, respectively. At the forest fringe, a similar result was found for H' (β1 = -218; P < 0.001) and PLAND (β1 = -337; P = 0.04). Anthropogenic changes in the Amazon vegetation classes decreased mosquito biodiversity, leading to increased Ny. darlingi abundance. Changes in landscape structure, specifically decreases in PLAND and increases in ED, led to Ny. darlingi becoming the dominant species, increasing malaria risk. Ecological mechanisms involving changes in landscape and mosquito species composition can help to understand changes in the epidemiology of malaria.

Predictors of malaria rapid diagnostic test positivity in a high burden area of Paletwa Township, Chin State in Western Myanmar

Background

Despite major reductions in malaria burden across Myanmar, clusters of the disease continue to persist in specific subregions. This study aimed to assess the predictors of test positivity among people living in Paletwa Township of Chin State, an area of persistently high malaria burden.

Methods

Four villages with the highest malaria incidence from Paletwa Township were purposively selected. The characteristics of 1045 subjects seeking malaria diagnosis from the four assigned village health volunteers from January to December, 2018 were retrospectively analyzed. Their household conditions and surroundings were also recorded using a checklist. Descriptive statistics and logistic regression models were applied to investigate potential associations between individual and household characteristics and malaria diagnosis.

Results

In 2017, the Paletwa township presented 20.9% positivity and an annual parasite index of 46.9 cases per 1000 people. Plasmodium falciparum was the predominant species and accounted for more than 80.0% of all infections. Among 1045 people presenting at a clinic with malaria symptoms, 31.1% were diagnosed with malaria. Predictors for test positivity included living in a hut [adjusted odds ratios (a OR): 2.3, 95% confidence intervals (CI): 1.2–4.6], owning farm animals (aOR: 1.7, 95% CI: 1.1–3.6), using non-septic type of toilets (aOR: 1.9, 95% CI: 1.1–8.4), presenting with fever (aOR: 1.9, 95% CI: 1.1–3.0), having a malaria episode within the last year (aOR: 2.9, 95% CI: 1.4–5.8), traveling outside the village in the previous 14 days (aOR: 4.5, 95% CI: 1.5–13.4), and not using bed nets (a OR: 3.4, 95% CI: 2.3–5.1). There were no statistically significant differences by age or gender in this present analysis.

Conclusions

The results from this study, including a high proportion of P. falciparum infections, little difference in age, sex, or occupation, suggest that malaria is a major burden for these study villages. Targeted health education campaigns should be introduced to strengthen synchronous diagnosis-seeking behaviors, tighten treatment adherence, receiving a diagnosis after traveling to endemic regions, and using bed nets properly. We suggest increased surveillance, early diagnosis, and treatment efforts to control the disease and then to consider the local elimination.

Prevalence and Risk Factors Associated with Malaria among Children Aged Six Months to 14 Years Old in Rwanda: Evidence from 2017 Rwanda Malaria Indicator Survey

Malaria is a major public health risk in Rwanda where children and pregnant women are most vulnerable. This infectious disease remains the main cause of morbidity and mortality among children in Rwanda. The main objectives of this study were to assess the prevalence of malaria among children aged six months to 14 years old in Rwanda and to identify the factors associated with malaria in this age group. This study used data from the 2017 Rwanda Malaria Indicator Survey. Due to the complex design used in sampling, a survey logistic regression model was used to fit the data and the outcome variable was the presence or absence of malaria. This study considered 8209 children in the analysis and the prevalence of malaria was 14.0%. This rate was higher among children aged 5-9 years old (15.6%), compared to other age groups. Evidently, the prevalence of malaria was also higher among children from poor families (19.4%) compared to children from the richest families (4.3%). The prevalence of malaria was higher among children from rural households (16.2%) compared to children from urban households (3.4%). The results revealed that other significant factors associated with malaria were: the gender of the child, the number of household members, whether the household had mosquito bed nets for sleeping, whether the dwelling had undergone indoor residual spraying in the 12 months prior to the survey, the location of the household's source of drinking water, the main wall materials of the dwelling, and the age of the head of the household. The prevalence of malaria was also high among children living in houses with walls built from poorly suited materials; this suggests the need for intervention in construction materials. Further, it was found that the Eastern Province also needs special consideration in malaria control due to the higher prevalence of the disease among its residents, compared to those in other provinces.

Spatio-Temporal Dynamic of Malaria Incidence: A Comparison of Two Ecological Zones in Mali

Malaria transmission largely depends on environmental, climatic, and hydrological conditions. In Mali, malaria epidemiological patterns are nested within three ecological zones. This study aimed at assessing the relationship between those conditions and the incidence of malaria in Dangassa and Koila, Mali. Malaria data was collected through passive case detection at community health facilities of each study site from June 2015 to January 2017. Climate and environmental data were obtained over the same time period from the Goddard Earth Sciences (Giovanni) platform and hydrological data from Mali hydraulic services. A generalized additive model was used to determine the lagged time between each principal component analysis derived component and the incidence of malaria cases, and also used to analyze the relationship between malaria and the lagged components in a multivariate approach. Malaria transmission patterns were bimodal at both sites, but peak and lull periods were longer lasting for Koila study site. Temperatures were associated with malaria incidence in both sites. In Dangassa, the wind speed (p = 0.005) and river heights (p = 0.010) contributed to increasing malaria incidence, in contrast to Koila, where it was humidity (p < 0.001) and vegetation (p = 0.004). The relationships between environmental factors and malaria incidence differed between the two settings, implying different malaria dynamics and adjustments in the conception and plan of interventions.

Variation of preventive practices and its association with malaria infection in eastern Indonesia: Findings from community-based survey

Background

Geographical variation may likely influence the effectiveness of prevention efforts for malaria across Indonesia, in addition to factors at the individual level, household level, and contextual factors. This study aimed to describe preventive practices at individual and a household levels applied by rural communities in five provinces in eastern Indonesia and its association with the incidence of malaria among adult (≥15 years) populations.

Methods

This study analyzed a subset of data of nationally representative community-based survey 2018 Riset Kesehatan Dasar (Riskesdas). Data for socio-demographic (age, gender, education and occupation) and preventive behaviors (use of mosquito bed nets while slept, insecticide-treated mosquito nets (ITNs), mosquito repellent, mosquito electric rackets, mosquito coil/electric anti-mosquito mats, and mosquito window screen) were collected. Data were analyzed using bivariate and multivariable logistic regression model.

Results

Total of 56,159 respondents (n = 23,070 households) living in rural areas in Maluku (n = 8044), North Maluku (n = 7356), East Nusa Tenggara (n = 23,254), West Papua (n = 5759) and Papua (n = 11,746) were included in the study. In the multivariable models, using a bed net while slept likely reduced the odds of self-reported malaria among Maluku participants. Reduced odds ratios of self-reported malaria were identified in those participants who used ITNs (North Maluku, ENT, Papua), repellent (Maluku, West Papua, Papua), anti-mosquito racket (ENT), coil (Maluku, North Maluku, Papua) and window screen (West Papua, Papua).

Conclusion

Our study concluded that the protective effects of preventive practices were varied among localities, suggesting the need for specific intervention programs.

Prevalence of Malaria and Associated Risk Factors Among Febrile Children Under Five Years: A Cross-Sectional Study in Arba Minch Zuria District, South Ethiopia

Background

Malaria is a major public health problem affecting humans, particularly in the tropics and subtropics. Children under 5 years old are the group most vulnerable to malaria infection because of less developed immune system. Countries have set targets that led to control and eliminate malaria with interventions of the at-risk groups, however malaria infection remained a major public health challenge in endemic areas.

Objective

This study aimed at determining the magnitude of malaria and associated factors among febrile children under 5 years old in Arba Minch “Zuria” district.

Methods

The study was conducted from April to May 2017. Blood samples were collected from 271 systematically selected febrile children under 5 years old. Thin and thick blood smears were prepared, stained with 10% Giemsa and examined under light microscope. Data of sociodemographic data, determinant factors, and knowledge and prevention practices of malaria were collected using a pretested structured questionnaire. Data were analyzed using binomial and multinomial regression model in SPSS^® Statistics program, version 25.

Results

Among those febrile children, 22.1% (60/271) were positive for malaria; 50.0%, 48.33% and 1.66% of them were positive for Plasmodium falciparum, Plasmodium vivax and mixed infections of both parasites, respectively. Malaria infection was associated with nearby presence of stagnant water to resident areas (AOR=8.19; 95%CI: 3.62-18.5, P<0.0001). Children who slept under insecticide-treated mosquito nets (ITNs) were more likely to be protected from malaria infection than those did not sleep under an ITNs (AOR=9.65; 95%CI: 4.623-20.15, P<0.0001).

Conclusion

Malaria infection is highly prevalent in children aged between 37 and 59 months old, in Arba Minch “Zuria” district. The proximity of residence to stagnant water and the use of ITNs are the most dominant risk factor for malaria infection. Improved access to all malaria interventions is needed to interrupt the transmission at the community level with a special focus on the risk groups.

Drinking water and sanitation conditions are associated with the risk of malaria among children under five years old in sub-Saharan Africa: A logistic regression model analysis of national survey data

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Drinking water and sanitation is a risk factor to malaria infection.

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Wealth brought mixed effects of the relationship between WS and malaria.

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The associations between WS and malaria were more pronounced among the non-poor children.

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This pooling multi-country data eliminates many bias seen in traditional meta-analysis.

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Improved drinking water and sanitation seemed to be promising in preventing malaria.

Current efforts for the prevention of malaria have resulted in notable reductions in the global malaria burden; however, they are not enough. Good hygiene is universally considered one of the most efficacious and straightforward measures to prevent disease transmission. This work analyzed whether improved drinking water and sanitation (WS) conditions were associated with a decreased risk of malaria infection. Data were acquired through surveys published between 2006 and 2018 from the Demographic and Health Program in sub-Saharan Africa (SSA). Multiple logistic regression was used for each national survey to identify the associations between WS conditions and malaria infection diagnosed by microscopy or a malaria rapid diagnostic test (RDT) among children (0–59 months), with adjustments for age, gender, indoor residual spraying (IRS), insecticide-treated net (ITN) use, house quality, and the mother’s highest educational level. Individual nationally representative survey odds ratios (ORs) were combined to obtain a summary OR using a random-effects meta-analysis. Among the 247,440 included children, 18.8% and 24.2% were positive for malaria infection based on microscopy and RDT results, respectively. Across all surveys, both unprotected water and no facility users were associated with increased malaria risks (unprotected water: aOR 1.17, 95% CI 1.07–1.27, P = 0.001; no facilities: aOR 1.35, 95% CI 1.24–1.47, P < 0.001; respectively), according to microscopy, whereas the odds of malaria infection were 48% and 49% less among piped water and flush-toilet users, respectively (piped water: aOR 0.52, 95% CI 0.45–0.59, P < 0.001; flush toilets: aOR 0.51, 95% CI 0.43–0.61, P < 0.001). The trends of individuals diagnosed by RDT were consistent with those of individuals diagnosed by microscopy. Risk associations were more pronounced among children with a “nonpoor” socioeconomic status who were unprotected water or no facility users. WS conditions are a vital risk factor for malarial infection among children (0–59 months) across SSA. Improved WS conditions should be considered a potential intervention for the prevention of malaria in the long term.