MATERIALS AND METHODS: This review has two parts. The first part is a scoping review of the factors associated with suicidal ideation and attempt among young people. The search was conducted in Pubmed, Scopus, and PsycInfo. The second part is the development of preventive strategies according to the identified factors. Both parts will be guided by the SEM model.
RESULTS: A total of ten studies with 45,278 participants that matched the criteria are included in this review. The review found that the risk factors for suicidal ideation among young people in LMIC are being female, psychiatric illness, psychology problem, smoking, alcohol intake, victim of abuse, bullied, and food insecurity. The preventive strategies include policy, mental healthcare services, awareness programme, and coping strategies.
CONCLUSION: More epidemiological studies are needed to evaluate the risk factors of suicide that are unique in LMIC, such as help-seeking behaviour and available mental healthcare services. Suicide prevention requires concerted effort of policymakers, healthcare services, community and individual; thus, SEM framework is suitable as a guidance for suicide prevention.
METHODS: This cross-sectional study was conducted in three Malaysian public hospitals namely Hospital Kuala Lumpur, Hospital Canselor Tuanku Muhriz and the National Cancer Institute using a multi-level sampling technique to recruit 630 respondents from February 2020 to February 2021. CHE was defined as incurring a monthly health expenditure of more than 10% of the total monthly household expenditure. A validated questionnaire was used to collect the relevant data.
RESULTS: The CHE level was 54.4%. CHE was higher among patients of Indian ethnicity (P = 0.015), lower level education (P = 0.001), those unemployed (P < 0.001), lower income (P < 0.001), those in poverty (P < 0.001), those staying far from the hospital (P < 0.001), living in rural areas (P = 0.003), small household size (P = 0.029), moderate cancer duration (P = 0.030), received radiotherapy treatment (P < 0.001), had very frequent treatment (P < 0.001), and without a Guarantee Letter (GL) (P < 0.001). The regression analysis identified significant predictors of CHE as lower income aOR 18.63 (CI 5.71-60.78), middle income aOR 4.67 (CI 1.52-14.41), poverty income aOR 4.66 (CI 2.60-8.33), staying far from hospital aOR 2.62 (CI 1.58-4.34), chemotherapy aOR 3.70 (CI 2.01-6.82), radiotherapy aOR 2.99 (CI 1.37-6.57), combination chemo-radiotherapy aOR 4.99 (CI 1.48-16.87), health insurance aOR 3.99 (CI 2.31-6.90), without GL aOR 3.38 (CI 2.06-5.40), and without health financial aids aOR 2.94 (CI 1.24-6.96).
CONCLUSIONS: CHE is related to various sociodemographic, economic, disease, treatment and presence of health insurance, GL and health financial aids variables in Malaysia.
METHODS: A total of 16,040 primary procedures were identified over a two-year period. Centers that submitted procedures were dichotomized to low/middle income (LMI) and high income (HI) by the Gross National Income per capita categorization. Mortality was defined as any death following the primary procedure to discharge or 90 days inpatient. Multiple logistic regression models were utilized to identify independent predictors of mortality.
RESULTS: Of the total number of procedures analyzed, 83% (n = 13,294) were from LMI centers. Among all centers, the mean age at operation was 2.2 years, with 36% (n = 5,743) less than six months; 85% (n = 11,307) of procedures were STAT I/II for LMI centers compared with 77% (n = 2127) for HI centers (P
METHODS: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.
FINDINGS: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000-257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.
INTERPRETATION: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution.
FUNDING: Bill & Melinda Gates Foundation.
METHODS AND ANALYSIS: We will conduct a systematic search in PubMed, Scopus, Web of Science and grey literature. Descriptive statistics will be used to report the characteristics of included studies. The facilitators and barriers to DHTs implementation, gathered from both quantitative and qualitative data, will be synthesised using a parallel-results convergent synthesis design. A thematic analysis, employing an inductive approach, will be conducted to categorise these facilitators and barriers into coherent themes. Additionally, we will identify and categorise all available DHTs based on their equipment types and methods of operation to develop an innovative classification framework.
ETHICS AND DISSEMINATION: Formal ethical approval is not required, as primary data collection is not involved in this study. The findings will be disseminated through peer-reviewed publications, conference presentations and meetings with key stakeholders and partners in the field of digital health.
DESIGN: In this study, a descriptive analysis was undertaken to describe seasonality trends and/or overlap between COVID-19 and influenza in 12 low-income and middle-income countries using Our World in Data and FluMart data sources. Plots of COVID-19 and influenza cases were analysed.
SETTING: Singapore, Thailand, Malaysia, the Philippines, Argentina, Brazil, Mexico, South Africa, Morocco, Bahrain, Qatar and Saudi Arabia.
OUTCOME MEASURES: COVID-19 cases and influenza cases.
RESULTS: No seasonal patterns of SARS-CoV-2 or SARS-CoV-2/influenza cocirculation were observed in most countries, even when considering the avian influenza pandemic period.
CONCLUSIONS: These results can inform public health strategies. The lack of observed seasonal behaviour highlights the importance of maintaining year-round vaccination rather than implementing seasonal campaigns. Further research investigating the influence of climate conditions, social behaviour and year-round preventive measures could be fundamental for shaping appropriate policies related to COVID-19 and respiratory viral disease control in low-income and middle-income countries as COVID-19 variant data and epidemiologic patterns accrue over time.
METHODS: MOOC participants were invited to take part in an anonymous online survey examining their knowledge of IR and how they applied it in their professional practice approximately 1-1.5 years after completing their course. The survey contained 43 open-ended, multiple choice and Likert-type questions. Descriptive statistics were calculated for the quantitative data and responses to the open-ended questions were thematically coded.
RESULTS: A total of 748 MOOC participants responded to the survey. The demographic profile of the survey respondents aligned with that of the MOOC participants, with nearly 70% of respondents originating from Africa. Responses to the quantitative and open-ended survey questions revealed that respondents' knowledge of IR had improved to a large extent as a result of the MOOC, and that they used the knowledge and skills gained in their professional lives frequently and had consequently changed their professional behaviour. Respondents most often cited the problem-solving aspect of IR as a substantial area of behavioral change influenced by participating in the MOOC.
CONCLUSIONS: These findings indicate that the MOOC was successful in targeting learners from LMICs, in strengthening their IR knowledge and contributing to their ability to apply it in their professional practice. The utility of MOOCs for providing IR training to learners in LMICs, where implementation challenges are encountered often, makes this platform an ideal standalone learning tool or one that could be combined with other training formats.
Methods: This is a qualitative study with a phenomenological approach. It starts with a literature review using large databases, followed by interviews with 10 representative experts from medical schools in Indonesia.
Results: Based on the 10 studies retrieved, several components of faculty development were identified as the basis for the model. Ten experts gave input for the model. Components of the model can be grouped into: (i) content, which is materials that need to be delivered; (ii) process components, which depict aspects related to the preparation, execution and evaluation of sustainable faculty development; and (iii) components in the educational system that affect faculty development implementation.
Conclusion: A comprehensive review and development process has likely made this faculty development model suitable for medical schools in Indonesia. Breaking the model into components may help medical schools to prioritise certain aspects related to faculty development programmes.
METHODS: PubMed, Science Direct, Scopus, and CINAHL databases were searched to find studies that examined FT. There was no limit on the design or setting of the study. Random-effects meta-analysis was utilized to obtain the pooled prevalence of objective FT.
RESULTS: Out of 244 identified studies during the initial screening, only 64 studies were included in this review. The catastrophic health expenditure (CHE) method was often used in the included studies to determine the objective FT. The pooled prevalence of CHE was 47% (95% CI: 24.0-70.0) in middle- and high-income countries, and the highest percentage was noted in low-income countries (74.4%). A total of 30 studies focused on subjective FT, of which 9 used the Comprehensive Score for FT (COST) tool and reported median scores ranging between 17.0 and 31.9.
CONCLUSION: This study shows that cancer patients from various income-group countries experienced a significant financial burden during their treatment. It is imperative to conduct further studies on interventions and policies that can lower FT caused by cancer treatment.
METHODS: Novel LMIC radiotherapy demand and outcome models were created by adjusting previously developed models that used HIC cancer staging data. These models were applied to the cancer case mix (ie, the incidence of each different cancer) in each LMIC in the Asia-Pacific region to estimate the current and projected optimal radiotherapy utilisation rate (ie, the proportion of cancer cases that would require radiotherapy on the basis of guideline recommendations), and to estimate the number of megavoltage machines needed in each country to meet this demand. Information on the number of megavoltage machines available in each country was retrieved from the Directory of Radiotherapy Centres. Gaps were determined by comparing the projected number of megavoltage machines needed with the number of machines available in each region. Megavoltage machine numbers, local control, and overall survival benefits were compared with previous data from 2012 and projected data for 2040.
FINDINGS: 57 countries within the Asia-Pacific region were included in the analysis with 9·48 million new cases of cancer in 2020, an increase of 2·66 million from 2012. Local control was 7·42% and overall survival was 3·05%. Across the Asia-Pacific overall, the current optimal radiotherapy utilisation rate is 49·10%, which means that 4·66 million people will need radiotherapy in 2020, an increase of 1·38 million (42%) from 2012. The number of megavoltage machines increased by 1261 (31%) between 2012 and 2020, but the demand for these machines increased by 3584 (42%). The Asia-Pacific region only has 43·9% of the megavoltage machines needed to meet demand, ranging from 9·9-40·5% in LMICs compared with 67·9% in HICs. 12 000 additional megavoltage machines will be needed to meet the projected demand for 2040.
INTERPRETATION: The difference between supply and demand with regard to megavoltage machine availability has continued to widen in LMICs over the past decade and is projected to worsen by 2040. The data from this study can be used to provide evidence for the need to incorporate radiotherapy in national cancer control plans and to inform governments and policy makers within the Asia-Pacific region regarding the urgent need for investment in this sector.
FUNDING: The Regional Cooperative Agreement for Research, Development and Training Related to Nuclear Science and Technology for Asia and the Pacific (RCA) Regional Office (RCARP03).