Key factors associated with malaria infection among patients seeking care through the public sector in endemic townships of Ayeyarwady Region, Myanmar

Forest-goers as a heterogeneous population at high-risk for malaria: a case-control study in Aceh Province, Indonesia

BACKGROUND

A major challenge to malaria elimination is identifying and targeting populations that are harbouring residual infections and contributing to persistent transmission. In many near-elimination settings in Southeast Asia, it is known that forest-goers are at higher risk for malaria infection, but detailed information on their behaviours and exposures is not available.

METHODS

In Aceh Province, Indonesia, a near-elimination setting where a growing proportion of malaria is due to Plasmodium knowlesi, a case-control study was conducted to identify risk factors for symptomatic malaria, characteristics of forest-goers, and key intervention points. From April 2017 to September 2018, cases and controls were recruited and enrolled in a 1:3 ratio. Cases had confirmed malaria infection by rapid diagnostic test or microscopy detected at a health facility (HF). Gender-matched controls were recruited from passive case detection among individuals with suspected malaria who tested negative at a health facility (HF controls), and community-matched controls were recruited among those testing negative during active case detection. Multivariable logistic regression (unconditional for HF controls and conditional for community controls) was used to identify risk factors for symptomatic malaria infection.

RESULTS

There were 45 cases, of which 27 were P. knowlesi, 17 were Plasmodium vivax, and one was not determined. For controls, 509 and 599 participants were recruited from health facilities and the community, respectively. Forest exposures were associated with high odds of malaria; in particular, working and sleeping in the forest (HF controls: adjusted odds ratio (aOR) 21.66, 95% CI 5.09-92.26; community controls: aOR 16.78, 95% CI 2.19-128.7) and having a second residence in the forest (aOR 6.29, 95% CI 2.29-17.31 and 13.53, 95% CI 2.10-87.12). Male forest-goers were a diverse population employed in a variety of occupations including logging, farming, and mining, sleeping in settings, such as huts, tents, and barracks, and working in a wide range of group sizes. Reported use of protective measures, such as nets, hammock nets, mosquito coils, and repellents was low among forest-goers and interventions at forest residences were absent.

CONCLUSIONS

Second residences in the forest and gaps in use of protective measures point to key malaria interventions to improve coverage in forest-going populations at risk for P. knowlesi and P. vivax in Aceh, Indonesia. Intensified strategies tailored to specific sub-populations will be essential to achieve elimination.

Comparison of deforestation and forest land use factors for malaria elimination in Myanmar

Objectives

Within the remote region of Ann Township in Myanmar's Rakhine State, malaria prevalence has remained steady at ∼10% of the population from 2016-2019. Previous studies have linked areas of higher malaria prevalence in the region to heavily forested areas, however, little is known about how people live, work, and move through these areas. This work aims to disentangle landscape from land use in regard to malaria exposure.

Methods

We investigated the roles of forest cover, forest loss, and land use activities with malaria prevalence through the combined use of land use surveys, malaria surveillance, and satellite earth observations.

Results

Our results confirm previous research that linked areas of high forest cover with high malaria prevalence. However, areas experiencing high levels of deforestation were not associated with malaria prevalence. The land use factors that contribute most significantly to increased malaria risk remained those which put people in direct contact with forests, including conducting forest chores, having an outdoor job, and having a primary occupation in the logging and/or plantation industry.

Conclusion

Malaria prevention methods in Myanmar should focus on anyone who lives near forests or engages in land use activities that bring them within proximity of forested landscapes, whether through occupation or chores.

Factors hindering coverage of targeted mass treatment with primaquine in a malarious township of northern Myanmar in 2019-2020

Targeted mass primaquine treatment (TPT) might be an effective intervention to facilitate elimination of vivax malaria in Myanmar by 2030. In this study, we explored the factors hindering coverage of a TPT campaign conducted in a malarious township of northern Myanmar. From August 2019 to July 2020, a cross-sectional exploratory design including quantitative and qualitative data was conducted in five villages with high P. vivax prevalence following a TPT campaign. Among a targeted population of 2322; 1973 (85.0%) participated in the baseline mass blood survey (MBS) and only 52.0% of the total targeted population (1208, 91.9% of total eligible population) completed the TPT. G6PD deficiency was found among 13.5% of total MBS participants and those were excluded from TPT. Of 1315 eligible samples, farmers and gold miners, males, and those aged 15 to 45 years had higher percentages of non-participation in TPT. Qualitative findings showed that most of the non-participation groups were outside the villages during TPT because of time-sensitive agricultural and other occupational or education-related purposes. In addition to mitigating of some inclusion criteria (i.e. including young children or offering weekly PQ treatment to G6PD deficient individuals), strengthening community awareness and increasing engagement should be pursued to increase community participation.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Risk factors associated with malaria infection along China–Myanmar border: a case–control study

Background

The World Health Organization (WHO) has certificated China malaria free, but imported malaria is a continuous challenge in preventing reintroduction of malaria in the border area of China. Understanding risk factors of malaria along China–Myanmar border is benefit for preventing reintroduction of malaria in China and achieving the WHO’s malaria elimination goal in the Greater Mekong Subregion (GMS).

Methods

This is a case–control study with one malaria case matched to two controls, in which cases were microscopy-confirmed malaria patients and controls were feverish people with microscopy-excluded malaria. A matched logistic regression analysis (LRA) was used to identify risk factors associated with malaria infection.

Results

From May 2016 through October 2017, the study recruited 223 malaria cases (152 in China and 71 in Myanmar) and 446 controls (304 in China and 142 in Myanmar). All the 152 cases recruited in China were imported malaria. Independent factors associated with malaria infection were overnight out of home in one month prior to attendance of health facilities (adjusted odd ratio [AOR] 13.37, 95% confidence interval [CI]: 6.32–28.28, P < 0.0001), staying overnight in rural lowland and foothill (AOR 2.73, 95% CI: 1.45–5.14, P = 0.0019), staying overnight at altitude < 500 m (AOR 5.66, 95% CI: 3.01–10.71, P < 0.0001) and streamlets ≤ 100 m (AOR9.98, 95% CI: 4.96–20.09, P < 0.0001) in the border areas of Myanmar; and people lacking of knowledge of malaria transmission (AOR 2.17, 95% CI: 1.42–3.32, P = 0.0004).

Conclusions

Malaria transmission is highly focalized in lowland and foothill in the border areas of Myanmar. The risk factors associated with malaria infection are overnight staying out of home, at low altitude areas, proximity to streamlets and lack of knowledge of malaria transmission. To prevent reintroduction of malaria transmission in China and achieve the WHO goal of malaria elimination in the GMS, cross-border collaboration is continuously necessary, and health education is sorely needed for people in China to maintain their malaria knowledge and vigilance, and in Myanmar to improve their ability of personal protection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04312-5.