Aging care is critical. Hence, the best-known newly developed technologies must be provided to the older population. This paper explains the need for mapping of strategies that must address preventive and promotional care and sickness management, empowering geriatric services, and guaranteeing optimal rehabilitation for the elderly population of India. Databases considered to carry out the literature review was Scopus, PubMed and Web of Science. Scientific articles published in English were only considered. Apart from scientific articles, government report, and newspaper articles, were also reviewed. Data was managed in Mendeley software. Articles based on elderly residing in urban populations and other age groups were excluded from the study. There are multiple barriers between the elderly beneficiaries and the healthcare services which stop the utilization of healthcare services. It can be demographic, aging, geographic, economic, accessibility, psychological, housing, transportation, medical, and social. Financial security is the top reason for not availing of healthcare services, followed by the perception that the ailment is not serious enough. The second reason was the unavailability of accessible healthcare facilities. Therefore, elderly people residing in rural regions, are more prone to varying diseases and are vulnerable to health inequity among other age groups in India. Considering the projected demography, it will only get worse until there is an intervention and feasible infrastructure, healthcare facilities, and services are provided in collaboration with local stakeholders and program monitors.

Background: Sociodemographic factors can significantly influence the knowledge level of tuberculosis (TB) patients, affecting the overall health outcomes. Due to lack of awareness and the stigma associated with TB, Indian TB elimination efforts are facing challenges. Patients with less information are more likely to experience delays in diagnosis and proper care. Method: A cross-sectional study was conducted in New Delhi across 26 operational National TB Elimination Program districts, involving 200 adult pulmonary TB patients receiving treatment from April to August 2020. A structured questionnaire guided the interviews, followed with bivariate analysis and descriptive statistics used for analysis. Results: Predominantly, residents of semiurban regions accounted for the highest proportion (70.5%), followed by urban areas (20.5%), with rural areas/slums comprising a minority (9%). Notably, a significant majority (94.5%) reported residing in individually owned dwellings, with shared accommodations limited to a minority (5.5%). Sanitary facilities varied, with 77% possessing personal toilets, 18.5% utilizing private facilities, and only 4.5% relying on public toilets. Awareness levels about TB reflected moderate awareness among 56% of participants, good knowledge among 41%, and minimal awareness (poor knowledge) among only 3% of respondents. Conclusion: Age, sex, socioeconomic level, kind of lodgings, malnutrition, and personal cleanliness should all be taken into account for TB treatment adherence. A new set of frameworks should be developed to enhance the living circumstances of high-risk populations and patients who are living in crowded locations since sharing a room or a house in a populated region increases the risk of TB transmission.

The initial step in suicide prevention involves identifying individuals who may be at risk of attempting suicide at an early stage. Utilising artificial intelligence (AI) and machine learning (ML) techniques offers innovative avenues for the early detection of such individuals. Nevertheless, there is a lack of clear information regarding the application of AI and ML in suicide prevention. Our objective is to examine the latest research findings on the utilization of AI/ML in forecasting suicidal tendencies. Authors reviewed four databases (PubMed/MEDLINE, Scopus, Web of Science and SCImago) for studies using AI/ML for suicide prevention published in English from 1 January 2000 to 31 December 2021. Search strings and MeSH were employed for searching terms relevant to suicide prevention and AI/ML. Results of the studies were analysed qualitatively, and information was presented as tables and figures. After removing duplicate articles, out of 434 studies, 21 articles, involving a total of 274,876 participants, met the inclusion criteria and were considered for this review. The results suggested that AI/ML-based suicide prediction models might improve healthcare systems by identifying individuals at high risk of suicide by preventing suicidal attempts. However, further researches are needed to perform AI/ML-based evidence-based assessment tools and determine their validity and reliability for suicide prediction models in different contexts.

The COVID-19 pandemic has significantly challenged healthcare systems worldwide, particularly in India, a country already burdened with a high prevalence of Neglected Tropical Diseases (NTDs). This perspective examines the pandemic’s direct and indirect impacts on the prevalence, diagnosis, and management of NTDs in India. Using a narrative review approach, we analyzed literature published between January 2020 and September 2023 from databases such as PubMed, Scopus, and Google Scholar, along with grey literature. The focus was on studies reporting the pandemic’s influence on NTDs, especially among vulnerable populations in both rural and urban settings. The review incorporated 49 studies, revealing a twofold impact of COVID-19 on India’s healthcare. Directly, the surge in COVID-19 cases strained healthcare resources, disrupted services, and overwhelmed healthcare personnel. Indirectly, the pandemic exacerbated the burden of NTDs by delaying diagnoses, limiting access to treatment, and redirecting resources toward pandemic response efforts. These findings highlight the urgent need for resilient healthcare strategies that address both the immediate and long-term impacts of the pandemic on NTDs. By understanding and mitigating these effects, policymakers and public health experts can better protect vulnerable populations from the compounded challenges posed by these neglected diseases.