AIMC Topic: Socioeconomic Factors

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Microclimates, land cover, and socioeconomic vulnerability shape Anopheles hotspots in Maryland, USA.

Infectious diseases of poverty
BACKGROUND: Anopheles mosquitoes pose notable public health concerns as competent vectors of malaria and other diseases. Although malaria is no longer endemic in the United States, recent locally acquired cases in states including Maryland highlight ...

Relationship between landslide susceptibility and social lag in Mexico City: The case of the west periphery.

PloS one
Landslides threaten sustainable development through economic and human losses. This study integrates machine learning methods to construct susceptibility maps, including topographic-hydrological indicators, to improve the inclusion of earthflow lands...

Identifying influential determinants of women's empowerment in Bangladesh using machine learning algorithms.

PloS one
BACKGROUND AND OBJECTIVES: Women's empowerment is a vital issue in lower-middle-income developing countries like Bangladesh, where it plays a pivotal role in advancing development across the nation. Thus, this study aimed to identify the influential ...

Machine learning identification of influencing factors of global Nation-Level hypertension prevalence.

BMC public health
Hypertension remains a critical global public health challenge, with its complex etiology poorly captured by traditional linear models, especially regarding macro-level structural and gender-specific drivers. To address this, we employed an interpret...

Formulation and validation of a regional household wealth index for sub-Saharan Africa.

PloS one
A new era in global health assistance requires a focus on efficiently using limited and declining donor funds. This shift requires better evaluation methods to allocate resources effectively. Most evaluations in low- and middle-income countries (LMIC...

Predictors of childhood vaccination uptake in England: an explainable machine learning analysis of regional data (2021-2024).

Vaccine
BACKGROUND: Childhood vaccination is a cornerstone of public health, yet disparities in vaccination coverage persist across England. These disparities arise from complex interactions among geographic, demographic, socioeconomic, and cultural (GDSC) f...

Reducing inequalities using an unbiased machine learning approach to identify births with the highest risk of preventable neonatal deaths.

Population health metrics
BACKGROUND: Despite contemporaneous declines in neonatal mortality, recent studies show the existence of left-behind populations that continue to have higher mortality rates than the national averages. Additionally, many of these deaths are from prev...

Applying machine learning to predict quality ANC determinants in Bangladesh: a BDHS-2022 cross-sectional study.

Scientific reports
Quality antenatal care (ANC) is critical for maternal and neonatal health. Despite improvements in healthcare, disparities in ANC access and quality persist, particularly in underserved areas of Bangladesh. This study aimed to identify the key determ...

Beyond health: A machine learning analysis of structural barriers to school attainment in Somalia.

PloS one
In fragile states like Somalia, the link between poor health and educational exclusion is critical yet poorly understood. This study uses a novel machine learning approach to identify and rank the most significant barriers to school attendance. We an...

Determinants of malaria transmission in Indian districts in 2018: insights from ensemble models.

Malaria journal
BACKGROUND: The National Framework for Malaria Elimination, formulated in 2016, aims to eliminate malaria in India by 2030, focusing on the districts as the strategic units for planning and implementing intervention measures. In this study, the spati...