Contact tracing for COVID-19 in a healthcare institution: Our experience and lessons learned

During the initial phases of the COVID-19 pandemic contact tracing was used to control spread of the disease. It played a key role in health care institute which continued to work even during lockdown. In this piece of work, we share the lessons learnt from the contact tracing activity done in the health care institution during April to July 2020. The training needs of persons involved in contact tracing, the follow of activities, use of technology, methods to fill the missing gaps were the key lessons learnt. Its documentation supports in setting up contact tracing activity for any emerging infectious disease outbreaks in future

Global, regional, and national burden of colorectal cancer and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Funding: F Carvalho and E Fernandes acknowledge support from Fundação para a Ciência e a Tecnologia, I.P. (FCT), in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy i4HB; FCT/MCTES through the project UIDB/50006/2020. J Conde acknowledges the European Research Council Starting Grant (ERC-StG-2019-848325). V M Costa acknowledges the grant SFRH/BHD/110001/2015, received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006.proofepub_ahead_of_prin

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Impact of COVID-19 on Psychological Status of General Population

WHO has declared COVID-19 as a pandemic on March 11, 2020. Like the virus affects the entire body, the pandemic affected the entire global trade and economy, leading to the loss of jobs and businesses. Thus, it would be appropriate to quote COVID-19 as a social disease rather than treating only as a medical condition. The COVID-19 pandemic, being a social disease, affects all the individuals of the society in terms of their physical, mental, social health and challenges the economic status of the entire population, irrespective of whether they were physically sick. However, the mental health impact of the COVID-19 pandemic has been overlooked, given its benign nature. We can anticipate a higher prevalence of psychological distress during any pandemic than typical situations. The COVID-19 instils fear and anxiety among people. Isolation and quarantine to reduce disease transmission have a negative impact on one’s mental health. The lockdowns lead to the closure of educational institutions and workplaces, loss of jobs, economic loss, lack of physical activity, restrictions on travel and gatherings. All these factors cumulatively affected the mental stamina of millions worldwide. Given its importance, we have reviewed the impact of COVID-19 on the psychological status of general population

Role of social support and spouse abuse in low birth weight: A Case–control study from Puducherry, India

Background: Low birth weight (LBW) is a major cause of neonatal morbidity and mortality. In addition to medical/clinical risk factors, various socio-demographic factors also have an impact on birth weight. Objective: The objective of the study is to determine the association of antenatal social support and spouse abuse during pregnancy with LBW in Urban areas of Puducherry. Materials and Methods: A community-based case–control study was conducted in Puducherry. Mothers of 100 LBW infants and normal birth weight infants in 2016 were studied. Functional Social Support Questionnaire and Index of Spouse Abuse scales were used. Conditional logistic regression for matched pair studies was done for multivariate analysis. Results: Mean (± standard deviation) age and education of the study participants was 25.6 (±3.5) and 8.28 (±3.6) years, respectively. The proportion of girl child was 59% and 43% among cases and controls, respectively. Mothers with higher perceived social support (odds ratio [OR] = 0.5; 95% confidence interval [CI]: 0.4–0.7) had lesser odds of LBW. The odds of LBW was 3.6 (adjusted OR [aOR] = 3.6; 95% CI: 1.3–9.9) times and 6.9 (aOR = 6.9; 95% CI: 1.5–31.9) times greater among mothers who experienced nonphysical abuse and had pregnancy-induced hypertension respectively and it was statistically significant after adjusting for child's gender, social support, and parity. Conclusions: The presence of nonphysical abuse during the antenatal period increased the risk of LBW. The awareness should be created in the community to prevent maternal exposure to abuse

Compliance with hand hygiene practices and its appropriateness among healthcare workers during COVID-19 pandemic in public health facilities of Tamil Nadu, India

Background: Compliance with appropriate hand hygiene practises is the most efficient and cost-effective intervention that can be implemented in the healthcare setting. Given its importance, we tried to capture the compliance with hand hygiene practises and their appropriateness among healthcare workers during the COVID-19 pandemic in public health facilities in Tamil Nadu. Methods: This cross-sectional study involved doctors, nurses, and allied healthcare professionals from various departments in 18 public healthcare facilities spanning six districts in Tamil Nadu. A random-intercept model was employed for the multivariable logistic regression analysis to evaluate the factors influencing hand hygiene compliance and its adequacy. The effect size was presented as an adjusted odds ratio (aOR) accompanied by a 95% confidence interval (CI). Results: In total, 2733 hand hygiene observations were made. Only during 19.4% (95%CI: 17.9%–20.9%) of these observations, hand washing was done. Only during 37.9% (95%CI: 33.9%–42.1%) of these observations, hand washing was done appropriately by following all the essential steps of hand hygiene. Nurses (aOR = 2.49; 95%CI: 1.90–3.26), healthcare workers in General Surgery (aOR = 2.18; 95%CI: 1.53–3.10) and Obstetrics & Gynaecology departments (aOR = 1.75; 95%CI: 1.26–2.43), working in inpatient departments (aOR = 2.64; 95%CI: 1.38–5.04) had significantly higher compliance to hand hygiene practices. Nurses (aOR = 2.58; 95%CI: 1.33–5.01) and General Medicine department healthcare workers (aOR = 1.98; 95%CI: 1.09–3.61) had significantly higher compliance to appropriate hand hygiene practices. Conclusion: Our study shows that only during one-fifth of the observations did healthcare workers do hand washing, and less than 10% did it appropriately by following all the essential steps of hand hygiene

Impact of second wave of COVID-19 pandemic on the hesitancy and refusal of COVID-19 vaccination in Puducherry, India: a longitudinal study

The second wave of COVID-19 pandemic has spread rampantly throughout India between April and May 2021, leading to high mortality rates. Identifying any change in the rate of vaccine hesitancy or refusal due to such mass casualty events will provide further insights on developing appropriate risk communication strategy. Hence, this study was undertaken to identify the vaccine hesitancy and refusal before and during the second wave of COVID-19 pandemic. We conducted a longitudinal study among 900 adults to know about their vaccine hesitancy and refusal pattern before (March 2021 – round-1) and during the second wave of COVID-19 pandemic (May 2021 – round-2). Telephonic interview was conducted using the pre-tested semi-structured questionnaire. There was an increase in the vaccine hesitancy (27.8% in round-1 to 32.7% in round-2) and refusal (25.6% in round-1 to 35.6% in round-2) during the second wave of pandemic in Puducherry. In adjusted analysis, vaccine hesitancy was found to increase by 1.19 times during the round-2 survey compared to round-1 survey (aIRR = 1.19; 95%CI: 1.03–1.37). We also found that the vaccine refusal increased by 1.40 times during the round-2 survey compared to round-1 survey (aIRR = 1.40; 95%CI: 1.22–1.62) after adjusting for age, place of residence, and occupation. We found that the confidence in COVID-19 vaccine efficacy and safety has declined over time leading to increase in the vaccine hesitancy and refusal in our study cohort, with more than one-third refusing to get themselves vaccinated during the second wave of pandemic

Screening for red flag symptoms of cancer: A community-based cross-sectional study from urban Puducherry, India

BACKGROUND: Patients with cancer often delay seeking medical advice in developing countries. In India, only 20%–30% of cancers are being diagnosed in Stages I and II. Screening for red flag symptoms of cancer can be used to identify high-risk individuals in the community. METHODOLOGY: A community-based cross-sectional study was conducted in February 2017 among 302 participants in one of the service areas of Jawaharlal Institute of Postgraduate Medical Education and Research urban health center selected by universal sampling. Data on the presence of red flag symptoms of cancer (persistent cough, persistent change in bowel/bladder habits, nonhealing ulcer, persistent difficulty in swallowing, unexplained weight loss, unexplained lump, persistent unexplained pain, unexplained bleeding, and change in the appearance of mole) and presence of risk factors were collected through interviews. The collected data were entered using EpiData version 3.0. RESULTS: The mean (standard deviation) age of the study participants was 44 (11) years and 50.6% of them were male. At least one red flag symptom of cancer was present in 22 (7.3%) individuals; 9 (2.8%) had unexplained pain, 4 (1.3%) had change in bowel habits, 4 (1.3%) had change in bladder habits, 3 (1%) had cough, 3 (1%) had nonhealing ulcer, 2 (0.6%) had unexplained bleeding, 1 (0.3%) had difficulty in swallowing, 1 (0.3%) had weight loss, 1 (0.3%) had lump, and 1 (0.3%) had change in the appearance of mole. CONCLUSION: Screening for red flag symptoms of cancer is an easy tool that can be used in the community to identify high-risk individuals, which will facilitate early diagnosis of cancer

Assessment of quality of life based on psychological, somatovegetative, and urogenital health problems among postmenopausal women in Urban Puducherry, South India: A cross-sectional observational study

Background: An average Indian woman spends almost one-third of her lifespan in the postmenopausal phase enduring the consequences of hormonal decline. This can have a significant impact on quality of life (QOL). Hence, this study was conducted to assess the QOL and health problems among postmenopausal women in urban Puducherry, South India. Methods: A cross-sectional study was carried out among postmenopausal women attending urban primary health center between April and May 2017. Information about social, economic, and demographic characteristics was collected using a semi-structured questionnaire, and menopause rating scale was used to assess the QOL. Results: Among 204 participants, 55.4% belonged to elderly age group (≥60 years); 61.3% did not have any formal education; 55.9% of the participants were unemployed; 68.7% were widowed, separated, or divorced; 89.7% belonged to Hindu religion; and 42.2% belonged to lower socioeconomic class. Majority (78%) suffered from psychological problems followed by somatovegetative (62%) and urogenital problems (33%). The prevalence of poor QOL was 37.2% (95% confidence interval: 30.8%–44.0%). Participants belonging to Hindu religion (annual percentage rate [aPR]-4.14), in nuclear family (aPR-2.31), and with chronic comorbidity (aPR-5.52) and alcohol/tobacco users (aPR-6.03) had significantly higher risk of poor QOL. Conclusion: The current study found that more than one-third of the postmenopausal women in urban Puducherry have poor QOL with majority suffering from psychological problems. Hence, more focus needs to be given to this target population to achieve physical, social, and mental well-being among females