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Publication Years
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Long-term exposure of humans to air pollution enhances the risk of cardiovascular and respiratory diseases. A novel Global Exposure Mortality Model (GEMM) has been derived from many cohort studies, providing much-improved coverage of the exposure to fine particulate matter (PM2.5). We applied the GE
...
MM to assess excess mortality attributable to ambient air pollution on a global scale and compare to other risk factors.
Methods and results
We used a data-informed atmospheric model to calculate worldwide exposure to PM2.5 and ozone pollution, which was combined with the GEMM to estimate disease-specific excess mortality and loss of life expectancy (LLE) in 2015. Using this model, we investigated the effects of different pollution sources, distinguishing between natural (wildfires, aeolian dust) and anthropogenic emissions, including fossil fuel use. Global excess mortality from all ambient air pollution is estimated at 8.8 (7.11–10.41) million/year, with an LLE of 2.9 (2.3–3.5) years, being a factor of two higher than earlier estimates, and exceeding that of tobacco smoking. The global mean mortality rate of about 120 per 100 000 people/year is much exceeded in East Asia (196 per 100 000/year) and Europe (133 per 100 000/year). Without fossil fuel emissions, the global mean life expectancy would increase by 1.1 (0.9–1.2) years and 1.7 (1.4–2.0) years by removing all potentially controllable anthropogenic emissions. Because aeolian dust and wildfire emission control is impracticable, significant LLE is unavoidable.
Conclusion
Ambient air pollution is one of the main global health risks, causing significant excess mortality and LLE, especially through cardiovascular diseases. It causes an LLE that rivals that of tobacco smoking. The global mean LLE from air pollution strongly exceeds that by violence (all forms together), i.e. by an order of magnitude (LLE being 2.9 and 0.3 years, respectively).
more
The Countdown country profiles present in one place the latest evidence to assess country progress in improving women’s, children’s and adolescents’ health. The profiles, including an interactive version of them and all associated
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data, can be found by viewing the latest country profile data.
more
The ECDC webpage on malaria provides an overview of the disease, emphasizing that while malaria is mostly travel-related in the EU/EEA, it remains a serious global health threat. It outlines symptoms, affected populations, travel-associated risks, a
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nd highlights the importance of prevention, surveillance, and data monitoring.
more
DHS Further Analysis Reports No. 111
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), ... health facility delivery, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery. more
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), ... health facility delivery, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery. more
The World Health Organization (WHO) endorses the use of population-based prevalence surveys for estimating the prevalence of trachoma. In general, the prevalence of TF in children aged 1–9 years and the prevalence of TT in adults aged ≥ 15 years
...
are measured at the same time in any district being surveyed. This was the approach of the Global Trachoma Mapping Project, which undertook baseline surveys in > 1500 districts worldwide in order to provide the data required to start interventions where needed.
The survey design recommended by WHO is a two-stage cluster random sample survey, which uses probability proportional to size sampling to select 20–30 villages, and random, systematic or quasi-random sampling to select 25–30 households in each of those villages. In most surveys, everyone aged ≥ 1 year living in selected households is examined. more
The survey design recommended by WHO is a two-stage cluster random sample survey, which uses probability proportional to size sampling to select 20–30 villages, and random, systematic or quasi-random sampling to select 25–30 households in each of those villages. In most surveys, everyone aged ≥ 1 year living in selected households is examined. more
Punjab Province Report: Nutrition Political Economy, Pakistan
Zaidi, Shehla; Bhutta, Zulfiqar et al.
Institute of Development Studies, Aga Khan University
(2015)
C1
In this report a nutrition governance framework was applied to research and analyse the provincial experience with nutrition policy in Pakistan, looking both at chronic and acute malnutrition. Twenty-one in-depth interviews with key stakeholders were also conducted along with a review of published a
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nd grey literature. Findings were validated and supplemented by consultative provincial roundtable meetings. Punjab’s nutritional puzzle is that it has high levels of chronic malnutrition and micro-nutrient deficiencies despite a surplus production of food and a low poverty level. Under-nutrition is mainly linked to insufficient attention to preventive health strategies and to a lack of connection between relevant sectors such as Education, Health, Poverty, Safe Water and Sanitation, and Food. Strategic opportunities are recommended which include cross-party political support and ownership for nutrition, with steering by executive leadership; multi-sectoral action and functional integration of various departments and programmes with the creation of a central convening structure for effective cross-sectoral coordination; broadening of nutritional activities beyond salt iodization and vitamin A coverage; central co-ordination of monitoring and evaluation and effective partnerships between the state and non-state sector around data production, awareness, advocacy, and monitoring.
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The World Population Dashboard showcases global population data, including fertility rate, gender parity in school enrolment, information on sexual and reproductive health, and much more. Together,
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these data shine a light on the health and rights of people around the world, especially women and young people. The numbers here come from UNFPA and fellow UN agencies, and are updated annually.
Accessed 26 February 2019
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More time or more money to improve nutrition in Benin Republic?
M. C. D. N. Vodouhe, L. Fakambi
Institut National des Recherches Agricoles du Bénin (INRAB)
(2015)
C2
Children malnutrition eradication in developing countries is a real challenge, especially among
vulnerable population. There are so many effort towards women (who are the main care providers)
socio-economic situation in order to improve their children nutrition. This article aims to identify the
...
impact of mothers’ activities on child nutrition and care. Interviews were used to collect data from
mothers of children less than 5 years old. Pearson correlation test and regression models were
performed to highlight relation and to identify the main factors that affect child nutrition and care. The
nutritional statuses of children show a high prevalence of underweight (38.46%), emaciation (25.17%)
and stunting (23.77%). Statistic results show that a child whose mother has food processing as main
activity has 2,322 more times to not suffer from emaciation malnutrition compared to a child whose
mother has trade as main activity. A child whose mother has high revenue has 1.463 more times to
not be suffering from stunting malnutrition compared to a child whose mother has lower revenue. A
child whose father has fishing as main activity has 8,4 more chance to not be suffering from stunting
malnutrition compared to a child whose father has another activity as main activity. A child whose
father is present in the household has 8.11 more chance to not suffer from stunting malnutrition
compared to a child whose father is absent. A child from mother who has food processing as main
activity is 2,464 more times preserved from fever compared to a child from mother whose main activity
is trade. Moreover child position, child feeding with porridge, child nursing are correlated with mother
activity. This situation is justified by the fact that mother need money to improve child nutrition and
health but they are also confronted to the fact that those activity that provide significant money are
sometime time consuming and not permit to take care of children in term of feeding practices, hygiene
control etc. Therefore it is important that intervention towards women take in consideration those
factors (money and time) but also the family in the whole.
more
Heart failure (HF) is a global public health concern with disproportionate socioeconomic, morbidity and mortality burden on low- and middle-income countries (LMICs). This review summarises contemporary dat
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a on the demographic and clinical characteristics, aetiologies, treatment, economic burden and outcomes of HF in LMICs. Patients with HF in LMICs are younger than those from high-income countries (HICs) and present at advanced stages of the disease. Hypertension, ischaemic heart disease (IHD), cardiomyopathy (CMO), and rheumatic heart disease (RHD) are the leading causes of HF in LMICs. The contribution of infectious diseases to HF remains prominent in many LMICs. Most health facilities in LMICs lack adequate diagnostic tools for HF, and the use of evidence-based medical and device therapies is suboptimal. Further, HF in LMICs is associated with prolonged hospital stay and high in-hospital and one-year mortality. Finally, HF has profound economic impact on individual patients who, mostly, have no health insurance, and on societies where patients are young, comprising those who have the greatest potential to contribute to economic productivity.
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Front Public Health . 2025 Jun 23:13:1609615. doi: 10.3389/fpubh.2025.1609615. eCollection 2025.
Key findings reveal the prevalent use of machine learning (ML), deep learning (DL), and natural language processing (NLP), which often integrate diver
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se data sources (e.g., epidemiological, web, climate, wastewater). The major benefits identified include earlier outbreak detection and improved prediction accuracy. However, significant challenges persist regarding data quality and bias, model transparency (the "black box" issue), system integration difficulties, and ethical considerations such as privacy and equity.
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Frontiers in Public Health, Vol.12 Nov 13;12:1455738. This review highlights RRML deployment procedures and addresses some critical challenges concerning their deployment. It suggests the provision of a pre-deployment logistics checklist, the use of
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a pre-determined standardized dataset for inputs to reduce data entry errors and the application of standardized internal and external quality assurance measures.
more
DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally us ... ed additive methods with a data reduction method—principal component analysis (PCA).
We scored the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index. more
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally us ... ed additive methods with a data reduction method—principal component analysis (PCA).
We scored the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index. more
Lesotho’s predominantly rural population faces significant health challenges within a setting of inadequate human resources for health. It is essential that nurses and nurse-midwives, who together
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make up the largest health workforce in the country, be adequately prepared to address Lesotho’s Health Priorities according to the Poverty Reduction Strategy Paper (PRSP) in the settings where they work. Under the HRAA project, Jhpiego conducted a task analysis study to obtain data on job duties or tasks performed by these cadres, as well as information about how often the tasks are performed, if and where tasks were learned, and the self-perceived level of competence in performing the tasks.
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Africa CDC Resource Website
recommended
Africa CDC strengthens the capacity and capability of Africa’s public health institutions as well as partnerships to detect and respond quickly and effectively to disease threats and outbreaks, based on
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data-driven interventions and programmes.
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Biodiversity and Health in the Face of Climate Change pp 47–66
This chapter reviews the emerging importance of pollen allergies in relation to ongoing climate change. Allergic diseases have been increasing in prevalence over the last decades, par
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tly as the result of the impact of climate change. Increased sensitisation rates and more severe symptoms have been the partial outcome of: increased pollen production of wind-pollinated plants resulting in long-term increased abundance of pollen in the air we breathe; earlier shifts of airborne pollen seasons making occurrence of allergic symptoms harder to predict and deal with efficiently; increased allergenicity of pollen causing more severe health effects in allergic individuals; introduction of new, invasive allergenic plant species causing new sensitisations; environment-environment interactions, such as plants and hosted microorganisms, i.e. fungi and bacteria, which comprise a complex and dynamic system, with additive, presently unforeseeable influences on human health; environment-human interactions, as the consequence of a combination of environmental factors, like air pollution, global warming, urbanisation and microclimatic variability, which create a multi-resolution spatiotemporal system that requires new processing technologies and huge data inflow in order to be thoroughly investigated. We suggest that novel, real-time, personalised pollen information services, like mobile-app risk alerts, must be developed to provide the optimum first line of allergy management.
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The main objective of the health systems is to meet the health needs of the population in general, but for this the system must have adequate financing and supply support to cover the entire populat
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ion in question and check quality, efficiency, equity services, safety and sustainability. However, considering the segmented Peruvian health system, this makes it more deficient in comprehensive care for the population due to the duplication of functions, misuse of its resources, absence of complementary services. Due to the COVID-19 pandemic, this deficiency in the Peruvian health system became more evident owing to the high number of
deaths and its state of collapse, combining these factors this scope review aims to map the current state of the Peruvian health system, its structure, synthesize data on the performance of the health system (in terms of access, coverage and quality of health services) and identify the main public health policies available
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Objective: To conduct a landscape assessment of public knowledge of cardiovascular disease risk factors and acute myocardial infarction symptoms, cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) awareness and training in three underserved communities in Brazil.
Metho
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ds: A cross-sectional, population-based survey of non-institutionalised adults age 30 or greater was conducted in three municipalities in Eastern Brazil. Data were analysed as survey-weighted percentages of the sampled populations.
Results: 3035 surveys were completed. Overall, one-third of respondents was unable to identify at least one cardiovascular disease risk factor and 25% unable to identify at least one myocardial infarction symptom. A minority of respondents had received training in CPR or were able to identify an AED. Low levels of education and low socioeconomic status were consistent predictors of lower knowledge levels of cardiovascular disease risk factors, acute coronary syndrome symptoms and CPR and AED use.
Conclusions: In three municipalities in Eastern Brazil, overall public knowledge of cardiovascular disease risk factors and symptoms, as well as knowledge of appropriate CPR and AED use was low. Our findings indicate the need for interventions to improve public knowledge and response to acute cardiovascular events in Brazil as a first step towards improving health outcomes in this population. Significant heterogeneity in knowledge seen across sites and socioeconomic strata indicates a need to appropriately target such interventions.
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Regional and global cholera surveillance is the continuous compilation of data from affected countries, analysis and interpretation at the regional and global levels, and prompt dissemination of findings for public
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health action.
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The ECDC's Cholera Monthly Surveillance page provides up-to-date data on cholera cases reported in Europe and globally. It monitors outbreaks, tracks trends, and analyzes the spread of the disease to support public
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health responses. The page includes interactive maps, statistics, and reports to help policymakers, researchers, and healthcare professionals understand cholera’s epidemiology and implement preventive measures.
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Front. Public Health 10:876949. doi: 10.3389/fpubh.2022.876949.In the present paper, the results of studying ML techniques in a tuberculosis diagnosis loop in a scenario of limited resources are presented.
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Data are analyzed using a tuberculosis (TB) therapy program at a health institution in a main city of a developing country using five ML models. Logistic regression, classification trees, random forest, support vector machines, and artificial neural networks are trained under physician supervision following physicians' typical daily work.
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