This commentary highlights the potential consequences of the COVID-19 pandemic for India’s rural population. The rural health care system in India is not adequate or prepared to contain COVID-19 ...transmission, especially in many densely populated northern Indian States because of the shortage of doctors, hospital beds, and equipment. The COVID-19 pandemic creates a special challenge due to the paucity of testing services, weak surveillance system and above all poor medical care. The impacts of this pandemic, and especially the lockdown strategy, are multi-dimensional. The authors argue for the need to take immediate steps to control the spread and its aftereffects and to use this opportunity to strengthen and improve its primary health care system in rural India.
ObjectivesTo estimate the antibiotic prescription rates for typhoid in India.DesignCross-sectional study.SettingPrivate sector primary care clinicians in India.ParticipantsThe data came from ...prescriptions of a panel of 4600 private sector primary care clinicians selected through a multistage stratified random sampling accounting for the region, specialty type and patient turnover. The data had 671 million prescriptions for antibiotics extracted from the IQVIA database for the years 2013, 2014 and 2015.Primary and secondary outcome measuresMean annual antibiotic prescription rates; sex-specific and age-specific prescription rates; distribution of antibiotic class.ResultsThere were 8.98 million antibiotic prescriptions per year for typhoid, accounting for 714 prescriptions per 100 000 population. Children 10–19 years of age represented 18.6% of the total burden in the country in absolute numbers, 20–29 year age group had the highest age-specific rate, and males had a higher average rate (844/100 000) compared with females (627/100 000). Ten different antibiotics accounted for 72.4% of all prescriptions. Cefixime–ofloxacin combination was the preferred drug of choice for typhoid across all regions except the south. Combination antibiotics are the preferred choice of prescribers for adult patients, while cephalosporins are the preferred choice for children and young age. Quinolones were prescribed as monotherapy in 23.0% of cases.ConclusionsNationally representative private sector antibiotic prescription data during 2013–2015 indicate a higher disease burden of typhoid in India than previously estimated. The total prescription rate shows a declining trend. Young adult patients account for close to one-third of the cases and children less than 10 years account for more than a million cases annually.
The consumption of antibiotics varies between and within countries. However, our understanding of the key drivers of antibiotic consumption is largely limited to observational studies. Using Indian ...data that showed substantial differences between states and changes over years, we conducted a quasi-experimental fixed-effects regression study to examine the determinants of private-sector antibiotic consumption. Antibiotic consumption decreased by 10.2 antibiotic doses per 1000 persons per year for every ₹1000 (US$12.9) increase in per-capita gross domestic product. Antibiotic consumption decreased by 46.4 doses per 1000 population per year for every 1% increase in girls' enrollment rate in tertiary education. The biggest determinant of private sector antibiotic use was government spending on health-antibiotic use decreased by 461.4 doses per 1000 population per year for every US$12.9 increase in per-capita government health spending. Economic progress, social progress, and increased public investment in health can reduce private-sector antibiotic use.
The aim of this study is to assess WHO/Eastern Mediterranean region (WHO/EMR) countries capacities, operations and outbreak response capabilities. Cross-sectional study was conducted targeting 22 ...WHO/EMR countries from May to June 2021. The survey covers 8 domains related to 15 milstones and key performance indicators (KPIs) for RRT. Responses were received from 14 countries. RRTs are adequately organised in 9 countries (64.3%). The mean retention rate of RRT members was 85.5% ± 22.6. Eight countries (57.1%) reported having standard operating procedures, but only three countries (21.4%) reported an established mechanism of operational fund allocation. In the last 6 months, 10,462 (81.9%) alerts were verified during the first 24 h. Outbreak response was completed by the submission of final RRT response reports in 75% of analysed outbreaks. Risk Communication and Community Engagement (RCCE) activities were part of the interventional response in 59.5% of recent outbreaks. Four countries (28.6%) reported an adequate system to assess RRTs operations. The baseline data highlights four areas to focus on: developing and maintaining the multidisciplinary nature of RRTs through training, adequate financing and timely release of funds, capacity and system building for implementing interventions, for instance, RCCE, and establishing national monitoring and evaluation systems for outbreak response.
Access to energy is an important social determinant of health, and expanding the availability of affordable, clean energy is one of the Sustainable Development Goals. It has been argued that climate ...mitigation policies can, if well-designed in response to contextual factors, also achieve environmental, economic, and social progress, but otherwise pose risks to economic inequity generally and health inequity specifically. Decisions around such policies are hampered by data gaps, particularly in low- and middle-income countries (LMICs) and among vulnerable populations in high-income countries (HICs). The rise of “big data” offers the potential to address some of these gaps. This scoping review sought to explore the literature linking energy, big data, health, and decision-making.
Literature searches in PubMed, Embase, and Web of Science were conducted. English language articles up to April 1, 2020, were included. Pre-agreed study characteristics including geographic location, data collected, and study design were extracted and presented descriptively, and a qualitative thematic analysis was performed on the articles using NVivo.
Thirty-nine articles fulfilled eligibility criteria. These included a combination of review articles and research articles using primary or secondary data sources. The articles described health and economic effects of a wide range of energy types and uses, and attempted to model effects of a range of technological and policy innovations, in a variety of geographic contexts. Key themes identified in our analysis included the link between energy consumption and economic development, the role of inequality in understanding and predicting harms and benefits associated with energy production and use, the lack of available data on LMICs in general, and on the local contexts within them in particular. Examples of using “big data,” and areas in which the articles themselves described challenges with data limitations, were identified.
The findings of this scoping review demonstrate the challenges decision-makers face in achieving energy efficiency gains and reducing emissions, while avoiding the exacerbation of existing inequities. Understanding how to maximize gains in energy efficiency and uptake of new technologies requires a deeper understanding of how work and life is shaped by socioeconomic inequalities between and within countries. This is particularly the case for LMICs and in local contexts where few data are currently available, and for whom existing evidence may not be directly applicable. Big data approaches may offer some value in tracking the uptake of new approaches, provide greater data granularity, and help compensate for evidence gaps in low resource settings.
Background and Objective
World Health Organization Eastern Mediterranean Region (WHO EMR) has 40% people in the world in need of humanitarian assistance. This systematic review explores selected ...vector-borne and zoonotic diseases (VBZDs) of importance to EMR in terms of disease burden across countries and periods, disaggregated across sex, age groups, education levels, income status, and rural/urban areas, related vector or animal source reduction measures, and public health, social and economic impacts and related interventions.
Methods
We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and reviewed articles in PubMed, Embase, and WHO Global Index Medicus published between 1st of January 2011 and 27th of June 2022. Thirteen VBZDs with at least one reported outbreak in the last five years in the region or prioritized as per previous analysis at the WHO global and regional level and based on expert consultations, were included as part of the analysis.
Results
The review included 295 studies—55% on leishmaniasis and dengue combined, and 75% studies from Pakistan, Kingdom of Saudi Arabia, and Iran combined. Hospital-based and nationally representative studies constituted 60% and 10% respectively. Males were predominantly affected in most diseases; children reported high burden of Leishmaniasis, whereas elderly had a higher burden of Dengue Fever and Middle East Respiratory Syndrome. Although very few studies reported on socioeconomic differences in burden, the ones that reported showed higher burden of diseases among the disadvantaged socioeconomic groups such as the poor and the less educated. More than 80% studies reported an increase in burden over the years.
Conclusion
The literature is scanty for most of the diseases reviewed and the number of studies from countries with humanitarian challenges is very low. The need for more nationally representative, population-based studies calls for prioritizing research investments.
Following mass traumatic events, greater exposure to traditional media like television (TV) about the event is associated with higher burden of post-traumatic stress disorder (PTSD). However, we know ...little about how social media exposure, combined with other media sources, shapes the population burden of PTSD following mass traumatic events.
We built a microsimulation of 1,18,000 agents that was demographically comparable to the population of Parkland and Coral Springs, Florida that experienced the Stoneman Douglas High School shooting in 2018. We parametrized the model using data from prior traumatic events and built an internal social network structure to facilitate the estimation of community PTSD prevalence following exposure to TV and social media coverage of the shooting.
Overall, PTSD prevalence in the community due to exposure to TV coverage of the shooting was 3.1%. Shifting the whole population's hours of TV watching to the lower half of the population distribution decreased PTSD prevalence to 1.3% while increasing TV watching to the upper half of the distribution increased the prevalence to 3.5%. Casual (i.e., viewing posts) social media use in addition to exposure to TV coverage increased PTSD prevalence to 3.4%; overall prevalence increased to 5.3% when agents shared videos related to the shooting on social media.
This microsimulation shows that availability and exposure to media coverage of mass traumatic events, particularly as social media becomes more ubiquitous, has the potential to increase community PTSD prevalence following these events. Future research could fruitfully examine the mechanisms that might explain these associations and potential interventions that can mitigate the role of media in shaping the mental health of populations following traumatic events.
Epidemiological studies on the prevalence and associated factors of cardiovascular diseases (CVDs) representative of all states of India among middle-aged and elderly are not much reported. The ...present study estimates the prevalence and associated factors of cardiovascular diseases across Indian states among men and women aged ≥45 years.
We used data from the Longitudinal Ageing Study in India wave 1 (2017–2019), which included a final analytical sample size of 56,935 adults and their spouses aged 45 years and above. We estimated CVDs prevalence for sociodemographic and behavioural variables, and multivariable logistic regression was used to assess the association between behavioural factors and CVDs in both men and women.
The prevalence of CVDs was 5.2% among adults ≥45 years (women: 4.6%; men: 5.9%), hypertension was 46.7% (women:48.9%; men:44%). Men and women have a similar prevalence of diabetes (11.9%) and cholesterol (2.3%). Prevalence of physical inactivity was 30.3% (women:27%; men:34.1%). Hypertension (adjusted odds ratio; aOR women:2.60, 95% CI: 2.08–3.25, men:1.88, 95% CI 1.54–2.29), hypercholesterolemia (aOR women:1.70; 95% CI 1.07–2.69, men 3.55; 95% CI 2.66–4.74), diabetes (aOR women:2.53; 95% CI 1.83–3.51, men:1.77 95% CI 1.44–2.17), obesity, physical inactivity, and smoking in men were significantly associated with CVDs.
The prevalence of CVDs and lifestyle risk factors among middle-aged and elderly poses severe concerns regarding noncommunicable disease (NCD) healthcare services provided in a lower-middle-income country like India. The key to preventing CVDs is controlling hypertension, diabetes, hypercholesterolemia, and increasing physical activity among adults aged ≥45 years.
Food is an important determinant of health, featuring prominently in the Sustainable Development Goals. The term “big data” is seldom used in relation to food, partly because food data are scattered ...across different sectors. The increasing availability of food-related data presents an opportunity to glean new insights on food and food systems. These insights may enhance the quality of products and services and improve decision-making on optimizing food availability, all to the end of producing better health. Yet, knowledge gaps remain about the unique opportunities and challenges linked to big data on food and their use in decision-making. This scoping review explored the available literature linking food with big data and decision-making, using the following research question: What is the current literature on data about food, and how are these data used in decision-making? We searched PubMed until 29 February 2020 and Embase, Web of Sciences, and the Cochrane Database of Systematic Reviews until 8 March 2020. We included studies written in English and conducted narrative analyses to identify relevant themes from included studies. Sixteen studies fulfilled our eligibility criteria, including big data analyses, modelling studies, and reviews. These studies described the added value of using big data and how evidence from big data had or can be used for decision-making, as well as challenges and opportunities for such use. The majority of the included studies examined the link between food and big data, while hypothesizing of how these insights could inform decision-making, including policies, interventions, programs, and financing. There were only two examples wherein big data on food informed decision-making directly. The review highlights several false dichotomies in how the subject is approached in the literature and the importance of context, both between and within countries, in shaping the availability and types of data that can be used as meaningful evidence to inform decision-making. This review shows the paucity of research around the intersection of food, big data, and decision-making, as well as the potential in using big data on food systems to the end of informing decisions to improve the health of populations. Future research and decision-making around health systems can benefit from examining the full spectrum of perspectives on the subject. Future research and decision-making around health systems can also employ the steadfast embrace of technology, which will potentially reduce disparities in big data availability, to the end of improving the health of populations.
Inappropriate use of antibiotics is a significant driver of antibiotic resistance in India. Largely unrestricted over-the-counter sales of most antibiotics, manufacturing and marketing of many ...fixed-dose combinations (FDC) and overlap in regulatory powers between national and state-level agencies complicate antibiotics availability, sales, and consumption in the country.
We analyzed cross-sectional data from PharmaTrac, a nationally representative private-sector drug sales dataset gathered from a panel of 9000 stockists across India. We used the AWaRe (Access, Watch, Reserve) classification and the defined daily dose (DDD) metrics to calculate the per capita private-sector consumption of systemic antibiotics across different categories: FDCs vs single formulations; approved vs unapproved; and listed vs not listed in the national list of essential medicines (NLEM).
The total DDDs consumed in 2019 was 5071 million (10.4 DDD/1000/day). Watch contributed 54.9% (2783 million) DDDs, while Access contributed 27.0% (1370 million). Formulations listed in the NLEM contributed 49.0% (2486 million DDDs); FDCs contributed 34.0% (1722 million), and unapproved formulations contributed 47.1% (2408 million DDDs). Watch antibiotics constituted 72.7% (1750 million DDDs) of unapproved products and combinations discouraged by the WHO constituted 48.7% (836 million DDDs) of FDCs.
Although the per-capita private-sector consumption rate of antibiotics in India is relatively low compared to many countries, India consumes a large volume of broad-spectrum antibiotics that should ideally be used sparingly. This, together with significant share of FDCs from formulations outside NLEM and a large volume of antibiotics not approved by the central drug regulators, call for significant policy and regulatory reform.
Not applicable.
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