Socio-economic and household determinants of malaria in adults aged 45 and above: analysis of longitudinal ageing survey in India, 2017-2018

Community perspective and healthcare assessment in malaria endemic states of India: a cross-sectional study protocol

INTRODUCTION

India's contribution to the malaria burden was highest in South-East Asia Region in 2021, accounting for 79% of the estimated malaria cases and 83% of malaria-related deaths. Intensified Malaria Control Programme supported by Global Funds to Fight against AIDS, Tuberculosis and Malaria has deployed crucial interventions to reduce the overall burden of malaria in India. Evaluation of utilisation of malaria elimination interventions by the community and assessment of the healthcare system is underway in eleven high malaria endemic states in India. Health system preparedness for malaria elimination, logistics, and supply chain management of diagnostic kits and anti-malarial drugs in addition to the knowledge, attitude and practice of the healthcare workers is also being assessed.

METHODS AND ANALYSIS

The study is being undertaken in 11 malaria endemic states with a variable annual parasite incidence of malaria. In total, 47 districts (administrative unit of malaria control operations) covering 37 976 households are to be interviewed and assessed. We present here the protocol following which the study is being undertaken at the behest and approval of Ministry of Health and Family Welfare in India.

ETHICS AND DISSEMINATION

No patients were involved in the study. Study findings will be shared with Institutional ethics board of National Institute for Malaria Research New Delhi (NIMR) in a timely, comprehensive, accurate, unbiased, unambiguous and transparent manner and to the National Vector-borne Disease (Malaria) Control Programme officers and the Community public who participated. Important findings will be communicated through community outreach meetings which are existing in the Health system. Results will be informed to study participants via local fieldwork supervised by District Malaria Officers. Also findings will be published in reputed journals based on Indian Council of Medical Research (ICMR) publication policy.The ICMR-NIMR ethics committee approved the study via letter No. NIMR/ECM/2023/Feb/14 dated 24 April 2023 for version 5. All standard ethical practices will be followed.

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.

The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India

The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively. The nonlinear associations between individual and synergistic effect of meteorological factors and malaria cases were assessed, and climate-based malaria prediction models were developed using the generalized additive model (GAM) with Gaussian distribution. During the study period, a total of 216,943 and 125,926 cases were recorded in Meghalaya and Tripura, respectively, and majority of the cases occurred due to the infection of Plasmodium falciparum in both the states. The temperature and relative humidity in Meghalaya and temperature, rainfall, relative humidity, and soil moisture in Tripura showed a significant nonlinear effect on malaria; moreover, the synergistic effects of temperature and relative humidity (SI=2.37, RERI=0.58, AP=0.29) and temperature and rainfall (SI=6.09, RERI=2.25, AP=0.61) were found to be the key determinants of malaria transmission in Meghalaya and Tripura, respectively. The developed climate-based malaria prediction models are able to predict the malaria cases accurately in both Meghalaya (RMSE: 0.0889; R²: 0.944) and Tripura (RMSE: 0.0451; R²: 0.884). The study found that not only the individual climatic factors can significantly increase the risk of malaria transmission but also the synergistic effects of climatic factors can drive the malaria transmission multifold. This reminds the policymakers to pay attention to the control of malaria in situations with high temperature and relative humidity and high temperature and rainfall in Meghalaya and Tripura, respectively.

Determinants of malaria infections among children in refugee settlements in Uganda during 2018-2019

BACKGROUND

While 5% of 247 million global malaria cases are reported in Uganda, it is also a top refugee hosting country in Africa, with over 1.36 million refugees. Despite malaria being an emerging challenge for humanitarian response in refugee settlements, little is known about its risk factors. This study aimed to investigate the risk factors for malaria infections among children under 5 years of age in refugee settlements in Uganda.

METHODS

We utilized data from Uganda's Malaria Indicator Survey which was conducted between December 2018 and February 2019 at the peak of malaria season. In this national survey, household level information was obtained using standardized questionnaires and a total of 7787 children under 5 years of age were tested for malaria using mainly the rapid diagnostic test. We focused on 675 malaria tested children under five in refugee settlements located in Yumbe, Arua, Adjumani, Moyo, Lamwo, Kiryadongo, Kyegegwa, Kamwenge and Isingiro districts. The extracted variables included prevalence of malaria, demographic, social-economic and environmental information. Multivariable logistic regression was used to identify and define the malaria associated risk factors.

RESULTS

Overall, malaria prevalence in all refugee settlements across the nine hosting districts was 36.6%. Malaria infections were higher in refugee settlements located in Isingiro (98.7%), Kyegegwa (58.6%) and Arua (57.4%) districts. Several risk factors were significantly associated with acquisition of malaria including fetching water from open water sources [adjusted odds ratio (aOR) = 1.22, 95% CI: 0.08-0.59, P = 0.002], boreholes (aOR = 2.11, 95% CI: 0.91-4.89, P = 0.018) and water tanks (aOR = 4.47, 95% CI: 1.67-11.9, P = 0.002). Other factors included pit-latrines (aOR = 1.48, 95% CI: 1.03-2.13, P = 0.033), open defecation (aOR = 3.29, 95% CI: 1.54-7.05, P = 0.002), lack of insecticide treated bed nets (aOR = 1.15, 95% CI: 0.43-3.13, P = 0.003) and knowledge on the causes of malaria (aOR = 1.09, 95% CI: 0.79-1.51, P = 0.005).

CONCLUSIONS

The persistence of the malaria infections were mainly due to open water sources, poor hygiene, and lack of preventive measures that enhanced mosquito survival and infection. Malaria elimination in refugee settlements requires an integrated control approach that combines environmental management with other complementary measures like insecticide treated bed nets, indoor residual spraying and awareness.

Altitude, not potential larval habitat availability, explains pronounced variation in Plasmodium falciparum infection prevalence in the western Kenya highlands

Progress in malaria control has stalled over the recent years. Knowledge on main drivers of transmission explaining small-scale variation in prevalence can inform targeted control measures. We collected finger-prick blood samples from 3061 individuals irrespective of clinical symptoms in 20 clusters in Busia in western Kenya and screened for Plasmodium falciparum parasites using qPCR and microscopy. Clusters spanned an altitude range of 207 meters (1077-1284 m). We mapped potential mosquito larval habitats and determined their number within 250 m of a household and distances to households using ArcMap. Across all clusters, P. falciparum parasites were detected in 49.8% (1524/3061) of individuals by qPCR and 19.5% (596/3061) by microscopy. Across the clusters, prevalence ranged from 26% to 70% by qPCR. Three to 34 larval habitats per cluster and 0-17 habitats within a 250m radius around households were observed. Using a generalized linear mixed effect model (GLMM), a 5% decrease in the odds of getting infected per each 10m increase in altitude was observed, while the number of larval habitats and their proximity to households were not statistically significant predictors for prevalence. Kitchen located indoors, open eaves, a lower level of education of the household head, older age, and being male were significantly associated with higher prevalence. Pronounced variation in prevalence at small scales was observed and needs to be taken into account for malaria surveillance and control. Potential larval habitat frequency had no direct impact on prevalence.

Social and housing indicators of dengue and chikungunya in Indian adults aged 45 and above: Analysis of a nationally representative survey (2017-18)

Background

Dengue and chikungunya (CHIKV) are the two major vector-borne diseases of serious public health concern in India. Studies on socioeconomic and housing determinants of dengue and CHIKV at a pan-India level are lacking. Here, we took advantage of the recently carried out Longitudinal Ageing Study in India (LASI) carried out across all the states and Union Territories of India to study the social indicators of dengue and CHIKV in India.

Methods

LASI-1 (2017-2018) data on the self-reported period prevalence of dengue and CHIKV from 70,932 respondents aged ≥45 years were used for this analysis. The state-wise distribution of dengue and CHIKV was mapped. Prevalence was estimated for each study variable, and the difference was compared using the χ2 test. The adjusted odds ratios (AOR) of the socioeconomic and housing variables for dengue and CHIKV were estimated using the multiple logistic regression model.

Results

Urban residence is the major socio-economic indicator of dengue and CHIKV (dengue AOR: 1.57, 95% CI: 1.18-2.11; CHIKV AOR: 1.84, 95% CI: 1.36-2.49). The other notable indicator is wealth; rich respondents have higher odds of dengue and CHIKV. Adults older than 54 years and those with high school education and above are associated with a lower likelihood of dengue and CHIKV. In addition, CHIKV is associated with scheduled and forward castes, households with improper toilet facilities, open defecation, and kutcha house type.

Conclusions

Despite the limitation that the data is only from adults ≥ 45, this analysis provides important insights into the socioeconomic and housing variables associated with higher odds of dengue and CHIKV in India. Understanding these determinants may assist in the national planning of prevention and control strategies for dengue and CHIKV.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00868-5.