IJID Regions

BackgroundSince the COVID-19 pandemic hit Indian states at varying speed, it is crucial to investigate the geographical pattern in COVID-19. We analyzed the geographical pattern of COVID-19 prevalence and mortality by the phase of national lockdown in India. MethodUsing publicly available compiled data on COVID-19, we estimated the trends in new cases, period-prevalence rate (PPR), case recovery rate (CRR), and case fatality ratio (CFR) at national, state and district level. FindingsThe age and sex are missing for more than 60 percent of the COVID-19 patients. There is an exponential increase in COVID-19 cases both at national and sub-national levels. The COVID-19 infected has jumped about 235 times (from 567 cases in the pre-lockdown period to 1,33,669 in the fourth lockdown); the average daily new cases have increased from 57 in the first lockdown to 6,482 in the fourth lockdown; the average daily recovered persons from 4 to 3,819; the average daily death from 1 to 163. From first to the third lockdown, PPR (0.04 to 5.94), CRR (7.05 to 30.35) and CFR (1.76 to 1.89) have consistently escalated. At state-level, the maximum number of COVID-19 cases is found in the states of Maharashtra, Tamil Nadu, Delhi, and Gujarat contributing 66.75 percent of total cases. Whereas no cases found in some states, Kerela is the only state flattening the COVID-19 curve. The PPR is found to be highest in Delhi, followed by Maharastra. The highest recovery rate is observed in Kerala, till second lockdown; and in Andhra Pradesh in third lockdown. The highest case fatality ratio in the fourth lockdown is observed in Gujarat and Telangana. A few districts viz. like Mumbai (96.7); Chennai (63.66) and Ahmedabad (62.04) have the highest infection rate per 100 thousand population. Spatial analysis shows that clusters in Konkan coast especially in Maharashtra (Palghar, Mumbai, Thane and Pune); southern part from Tamil Nadu (Chennai, Chengalpattu and Thiruvallur), and the northern part of Jammu & Kashmir (Anantnag, Kulgam) are hot-spots for COVID-19 infection while central, northern and north-eastern regions of India are the cold-spots. ConclusionIndia has been experiencing a rapid increase of COVID-19 cases since the second lockdown phase. There is huge geographical variation in COVID-19 pandemic with a concentration in some major cities and states while disaggregated data at local levels allows understanding geographical disparity of the pandemic, the lack of age-sex information of the COVID-19 patients forbids to investigate the individual pattern of COVID-19 burden. Major highlights of the studyO_LIThe new cases of COVID-19 have increased exponentially since the second lockdown phase in India. There is consistent improvement in the recovery rate (CRR is 7.1 percent in pre-lockdown to 44.0 percent in fourth lockdown period) with a low level of CFR (1.87 percent as of May 29st 2020). C_LIO_LIAt the state level, the most vulnerable states for the COVID-19 crisis are the state of Maharashtra, Tamil Nadu, Delhi, and Gujarat contributing 66.75 percent of total cases. C_LIO_LIThe PPR is found to be highest in Delhi, followed by Maharastra. While the highest recovery rate is observed in Kerala, the highest case fatality ratio in the fourth lockdown is observed in Gujarat and Telangana. The top 10 hotspot districts in India account for 58.3 percent of the new cases. Among them, Mumbai has the highest infection rate of 96.77 per 100 thousand, followed by Chennai with 63.66 per 100 thousand, and Ahmedabad with 62.04 per 100 thousand. C_LIO_LIThe information on age and sex are missing for more than 60 percent of the patients. C_LI

BackgroundCoronavirus disease 2019 (COVID-19) has emerged as a pandemic, and the infection due to SARSCoV-2 has now spread to more than 200 countries3. Surveillance systems form the foundation stone of active case finding, testing and contact tracing, which are the key components of the public health response to this novel, emerging infectious disease4. There is uncertainty about the true proportion of patients who remain asymptomatic or pre-symptomatic at a given time. As per the WHO-China Joint Monitoring Mission Report, and an analysis of 21 published reports, anywhere between 5 and 80 per cent of SARS-CoV-2-infected patients have been noted to be asymptomatic5, 6 Whereas in India 4197563 cases are positive, in which in West Bengal total 180788 cases(4.04% of Cases of India) positive of COVID 19. In Paschim Medinipur (West Medinipur) district contributing total 5489 cases (3.03% cases of West Bengal)9,10,11. In this scenario, we want to know the status of IgG seroprevalence of SARS-CoV-2 among asymptomatic general population, so that we can determine the extent of infection of SARS-CoV-2 in general population. ObjectivesPrimary Objective:- To estimate the seroprevalence for SARS-CoV-2 infection in the general asymptomatic population at Paschim Medinipur District. Secondary Objectives-To estimate age and sex specific seroprevalence. To determine the socio demographic risk factors for SARS-CoV-2 infection; To determine the other risk factors like comorbidities, vaccination status, travel history, contact history etc.; To determine the durability of Immunity (IgG) conferred by natural infection of SARS-CoV-2 in individuals previously RTPCR positive. MethodologyIt was a cross sectional 30 cluster study among the population of Paschim Medinipur district of West Bengal conducted in last week of July and 1st week of August 2020 among 458 asymptomatic general population and 30 RTPCR positive cases in 30 villages or wards of municipalities. 30 clusters were chosen from list of COVID 19 affected villages/wards of municipality as per PPS (Probability Proportional to Size) method. ResultsOf the 458 asymptomatic general population,19 asymptomatic people found to be seropositive IgG for SARS-CoV-2 with Mean or average total seropositivity rate of 4.15%. 19 Out of 30 (63.33%) RTPCR positive patients found Seronegative. Median of Days between RTPCR test and sero negativity found was 60 with minimum 28 days to maximum 101 days and Range of 73 days and a standard deviation of 19.46. Among risk factors, the risk of having IgG is more in persons having Travel history with odds ratio of 2.99-95%CI (1.17-7.65) with p-value-0.02. Hydroxychloroquine prophylaxis with Odds ratio of 8.49-95% CI(1.59-45.19) with p value - 0.003. Occupation as migrant labour with Odds ratio of 5.08-95% CI(1.96-13.18) with p value of 0.001. H/O Chicken pox with Odds ratio of 2.15-95% CI(0.59-7.79) with p value of 0.017. Influenza vaccinated with Odds ratio of 8.07 with 95% CI (0.8-81.48) with a p value of 0.036. ConclusionOf the 458 asymptomatic general population,19 asymptomatic people found to be seropositive IgG for SARS-CoV-2 with Mean or average total seropositivity rate of 4.15%. 19 Out of 30 (63.33%) RTPCR positive patients found Seronegative. Median of Days between RTPCR test and sero negativity found was 60 with minimum 28 days to maximum 101 days and Range of 73 days and a standard deviation of 19.46. Those having Travel History and having occupation as Migrant Labourer - have significantly higher probability of getting infected with SARS-CoV-2. No role has been found of Hydroxychloroquine Medicines as Chemoprophylactic. No durable immunity conferred by natural infection with SARS-CoV-2 -mean time to become seronegative after positive RTPCR test 60 days. So there is a chance of reinfection after average 2 months.

BackgroundInvestigation of the effect of SARS-CoV-2 variants and COVID-19 vaccination on inflammatory and immune response to SARS-CoV-2 infection is limited in South Asia. ObjectivesWe aimed to examine the impact of COVID-19 vaccination and waves of COVID- 19 on inflammatory and immunological biomarkers among COVID-19 patients in India. MethodsThis cross-sectional analysis used baseline data from a randomized controlled trial of vitamin D and zinc during COVID-19 infection in India (N=181). Blood samples and data regarding vaccination doses were collected. The second (Delta) or third (Omicron) wave was determined by date of enrolment. Mixed effects linear regression with robust standard errors was used to examine associations between COVID-19 vaccination dose or wave at enrolment and C-Reactive Protein (CRP), ferritin, lactate dehydrogenase (LDH), D-dimer, interleukin-6 (IL-6), angiopoietin-2 (Ang-2), soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), immunoglobulin G (IgG) and immunoglobulin M (IgM). ResultsCompared to no vaccination, full vaccination was associated with lower LDH (P<0.001), D-dimer (P=0.521) and Ang-2 (P=0.046), and higher IgG levels (P<0.001). Partial vaccination was associated with lower IL-6 (P=0.040) and higher IgG (P<0.001). Enrolment during the third wave was associated with lower IL-6 (P<0.001), CRP (P=0.056), IgM (P=0.013), and IgG (P<0.001), but higher D-dimer levels (P<0.001). ConclusionsCOVID-19 vaccination status and SARS-CoV-2 variant influence the inflammatory and immunologic response during SARS-CoV-2 infection, contributing to the severity of clinical presentation.

Background & ObjectiveSocial determinants of evolving covid-19 pandemic have not been well studied. To determine trends in transition of this epidemic in India we performed a study in states at various levels of human development index (HDI). MethodsWe used publicly available data sources to track progress of covid-19 epidemic in India in different states and territories where it was reported in significant numbers. The states (n=20) were classified into tertiles of HDI and weekly trends in cases and deaths plotted from 15 March to 2 May 2020. To assess association of HDI with state-level covid-19 burden we performed Pearsons correlation. Logarithmic trends were evaluated for calculation of projections. A microlevel study was performed in select urban agglomerations for identification of socioeconomic status (SES) differentials. ResultsThere is wide regional variation in covid-19 cases and deaths in India from mid-March to early-May 2020. High absolute numbers have been reported from states of Maharashtra, Gujarat, Delhi, Madhya Pradesh, Rajasthan and Tamilnadu. Growth rate in cases and deaths is slow in high HDI states while it has increased rapidly in middle and lower HDI states. In mid-March 2020 there was a strong positive correlation of state-level HDI with weekly covid-19 cases (r= 0.37, 0.40) as well as deaths (r= 0.31, 0.42). This declined by early-May for cases (r= 0.04, 0.06) as well as deaths (r= - 0.005, 0.001) with significant negative logarithmic trend (cases R squared= 0.92; deaths R squared= 0. 84). These trends indicate increasing cases and deaths in low HDI states. Projection reveals that this trend is likely to continue to early-June 2020. Microlevel evaluation shows that urban agglomerations are major focus of the disease in India and it has transited from middle SES to low SES locations. ConclusionThere is wide variability in burden of covid-19 in India. Slow growth and flattening of curve is observed in high-HDI states while disease is increasing in mid and lower HDI states. Projections reveal that lower HDI states would achieve parity with high HDI states by early-June 2020. Covid-19 is mostly present in urban agglomerations where it has transited from upper-middle to low SES locations. Public health strategies focusing on urban low SES locations and low HDI states are crucial to decrease covid-19 burden in India.

BackgroundIndia is vulnerable to community infection of COVID-19 due to crowded and poor living condition, high density, slums in urban areas and poor health care system. The number of COVID 19 infection has crossed 300,000 with over 7,500 deaths despite a prolonged period of lock down and restrictions in public spaces. Given the likely scale and magnitude of this pandemic, it is important to understand its impact on the age pattern of mortality under varying scenarios. ObjectiveThe main objective of this paper is to understand the age pattern of mortality under varying scenarios of community infection. Data and MethodsData from the Sample Registration System (SRS), covidi19india.org and country specific data from worldmeter is used in the analyses. Descriptive statistics, case-fatality ratio, case fatality ratio with 14 days delay, abridged life table,years of potential life lost (YPLL) and disability adjusted life years (DALY) is used. ResultsThe case fatality ratio (CFR) with 14 days delay for India is at least twice higher (8.0) than CFR of 3.4. Considering 8% mortality rate and varying scenario of community infection by 0.5%, 1% and 2%, Indias life expectancy will reduce by 0.8, 1.5 and 3.0 years and potential life years lost by 12.1 million, 24.3 million and 48.6 million years respectively. A community infection of 0.5% may result in DALY by 6.2 per 1000 population. Major share of PYLL and DALY is accounted by the working ages. ConclusionCOVID-19 has a visible impact on mortality with loss of productive life years in working ages. Sustained effort at containing the transmission at each administrative unit is recommended to arrest mortality owing to COVID-19 pandemic. What is known?The case fatality rate associated with COVID-19 is low in India compared to many other countries. The mortality level is higher among elderly and people with co-morbidity. ContributionThe case fatality ratio is illusive in the sense that the same with 14 days delay for India is at least twice higher (8.0). The COVID-19 attributable mortality has the potential to reduce the longevity of the population. Unlike developed countries, about half of the COVID-19 attributable mortality would be in the working age group of 45-64 years. With any level of community infection, the years of potential life lost (YPLL) and disability adjusted life years (DALY) world be highest in the working age group (45-64 years).

Sub Saharan Africa (SSA) harbours more than 80% of adolescents living with HIV. High age of consent for HIV testing has been identified as one of the key barriers to adolescents access to HIV testing. We conducted a systematic literature review to demonstrate the status of age of consent policies in SSA and evidence of relationship between age of consent policies and adolescents uptake of HIV testing. We obtained peer reviewed literature from Medline, Embase, Scopus and Web of Science databases and policy review from national HIV testing guidelines and UNAIDS data reports. Age of consent for HIV testing in the region ranged between 12 and 18 years. Among 33 included countries, 14 (42.4%) had age of consent between 12 - 14 years, 9 (27.3%) had age of consent between 15 - 17 years and 10 countries (30.3%) still have the highest age of consent at 18 years as of 2019. Lowering age of consent has been associated with increased access to HIV testing among adolescents.

Background & AimWHO listed vaccine hesitancy among the top 10 global threats to health and there are very few reports highlighting vaccine benefits against COVID-19. The aim of this study was to study the impact of vaccination on reducing the average length of stay (ALOS), intensive care unit (ICU) requirement, mortality and cost of the treatment among COVID-19 patients. MethodsIn this retrospective cohort study all the patients above 45 years who underwent treatment for COVID-19 were included. The data of patients treated pan India during the period March & April 2021 with the diagnosis of COVID-19, under health insurance cover, were extracted to study parameters like the ALOS, mortality, ICU requirement, total hospital expenses incurred and the vaccination status. ResultsAmong 3820 patients with COVID-19, 3301 (86.4%) were unvaccinated while 519 (13.6%) were vaccinated. Among the unvaccinated the mean (s.d) ALOS was 7 days. Fourteen days after second dose of vaccination this was significantly less (p=0.01) at 4.9. The mean total hospital expense among the unvaccinated was Rs. 277850. Fourteen days after second dose of vaccination this was further less (p=0.001) at Rs. 217850. Among the unvaccinated population 291/3301 (8.8%) required ICU and this was significantly less (p=0.03) at 31/519 (6%) among the vaccinated. Among those who received two doses of vaccination it was further less at 1/33 (3%). The mortality among unvaccinated patients was 16/3301 (0.5%) while there was no mortality among the vaccinated. Among those who received two doses of vaccination there was a 66% relative risk reduction in ICU stay and 81% relative risk reduction in mortality. ConclusionsThere was a significant reduction in ALOS, ICU requirement, mortality & treatment cost in patients who had completed two doses of vaccination. These findings may be used in motivating public and promoting vaccination drive.

IntroductionThe outbreak of COVID-19 has differentially affected countries in the world, with health infrastructure and other related vulnerability indicators playing a role in determining the extent of the COVID-19 spread. Vulnerability of a geographical region/country to COVID-19 has been a topic of interest, particularly in low- and middle-income countries like India to assess the multi-factorial impact of COVID-19 on the incidence, prevalence or mortality data. Datasets and MethodsBased on publicly reported socio-economic, demographic, health-based and epidemiological data from national surveys in India, we compute contextual, COVID-19 Vulnerability Indices (cVIs) across multiple thematic resolutions for different geographical and spatial administrative regions. These multi-resolution cVIs were used in regression models to assess their impact on indicators of the spread of COVID-19 such as the average time-varying instantaneous reproduction number. ResultsOur observational study was focused on 30 districts of the eastern Indian state of Odisha. It is an agrarian state, prone to natural disasters and one of the largest contributors of an unprotected migrant workforce. Our analyses identified housing and hygiene conditions, availability of health care and COVID preparedness as important spatial indicators. ConclusionOdisha has demonstrated success in containing the COVID-19 infection to a reasonable level with proactive measures to contain the spread of the virus during the first wave. However, with the onset of the second wave of COVID, the virus has been making inroads into the hinterlands and peripheral districts of the state, burdening the already deficient public health system in these areas. The vulnerability index presented in this paper identified vulnerable districts in Odisha. While some of them may not have a large number of COVID-19 cases at a given point of time, they could experience repercussions of the pandemic. Improved understanding of the factors driving COVID-19 vulnerability will help policy makers prioritise resources and regions leading to more effective mitigation strategies for the COVID-19 pandemic and beyond. O_TEXTBOXWHAT IS ALREADY KNOWNMeasuring vulnerability to COVID-19 and other pandemics is a complex and layered subject. In Low-to-Middle-Income Country (LMIC) like India, complete reliance on incidence, prevalence or mortality data of the disease may not be the best measure since this data from the health system and DHS in public domain is limited. ADDED VALUE OF THIS STUDYTo our knowledge, this is the first study at the district level concerning the COVID-19 situation in Odisha, characterized by a large tribal and migrant population. We defined vulnerability through relevant socio-economic domains that have an influence on mitigation strategies. Although we applied our methods to the districts of Odisha, we believe they can be used in other LMIC regions. IMPLICATIONS OF THE FINDINGSRegions with higher overall or theme-specific vulnerability index might experience potentially severe consequences of the COVID-19 outbreak demanding precise, dynamic and nimble policy decisions to prevent a potentially dire situation. C_TEXTBOX

Back groundHIV/AIDS remained among the common public health problems worldwide. Despite the extensive delivery of ART and improved coverage of the service access, still, man-made problems like war have negatively influenced the utilization of antiretroviral treatment services. The war in Tigray Region in the northern Ethiopia broke out in November 2020 and thereby has brought about an extreme damage on most of the infrastructure in Tigray, including the health institutions. The purpose of this study is, therefore, to assess and report the trend of HIV service provision across the war affected rural health facilities in Tigray. MethodsThe study was conducted in 33 rural health facilities during the active war in Tigray. A facility based retrospective cross-sectional study design was conducted among health facilities from July 03 to August 05, 2021. ResultA total of 33 health facilities from 25 rural districts were included in the HIV service delivery assessment. A total of 3274 and 3298 HIV patients were seen during pre-war period in September and October 2020, respectively. The number of follow-up patients during the war period in January remained to be only 847(25%) which is significantly reduced with a P value<0.001. A similar trend was observed during the subsequent months until May. The trend of follow-up patients on ART significantly declined from 1940 in September (pre-war) to 331(16.6%) in May (during the war). This study also revealed a 95.5% reduction of laboratory service provision to HIV/AIDS patients during the war in January and with similar trends thereafter (P<0.001). ConclusionThe war has led to a significant decline of HIV service provision in the rural health facilities and most part of the region during the first eight months of active war in Tigray.

Second wave of COVID-19 pandemic in India came with unexpected quick speed and intensity, creating an acute shortage of beds, ventilators, and oxygen at the peak of occurrence. This may have been partly caused by emergence of new variant delta. Clinical experience with the cases admitted to hospitals suggested that it is not merely a steep rise in cases but also possibly the case-profile is different. This study was taken up to investigate the differentials in the characteristics of the cases admitted in the second wave versus those admitted in the first wave. Records of a total of 14398 cases admitted in the first wave (2020) to our network of hospitals in north India and 5454 cases admitted in the second wave (2021) were retrieved, making it the largest study of this kind in India. Their demographic profile, clinical features, management, and outcome was studied. Age-sex distribution of the cases in the second wave was not much different from those admitted in the first wave but the patients with comorbidities and those with greater severity had larger share. Level of inflammatory markers was more adverse. More patients needed oxygen and invasive ventilation. ICU admission rate remained nearly the same. On the positive side, readmissions were lower, and the duration of hospitalization was slightly less. Usage of drugs like remdesivir and IVIG was higher while that of favipiravir and tocilizumab was lower. Steroid and anticoagulant use remained high and almost same during the two waves. More patients had secondary bacterial and fungal infections in Wave-2. Mortality increased by almost 40% in Wave-2, particularly in the younger patients of age less than 45 years. Higher mortality was observed in those admitted in wards, ICU, with or without ventilator support and those who received convalescent plasma. No significant demographic differences in the cases in these two waves, indicates the role of other factors such as delta variant and late admissions in higher severity and more deaths. Comorbidity and higher secondary bacterial and fungal infections may have contributed to increased mortality.

ObjectivesThis study aims to describe the demographic and clinical profile and ascertain the determinants of outcome among hospitalised COVID-19 adult patients enrolled in the National Clinical Registry for COVID-19 (NCRC). MethodsNCRC is an on-going data collection platform operational in 42 hospitals across India. Data of hospitalized COVID-19 patients enrolled in NCRC between 1st September 2020 to 26th October 2021 were examined. ResultsAnalysis of 29,509 hospitalised, adult COVID-19 patients [mean (SD) age: 51.1 (16.2) year; male: 18752 (63.6%)] showed that 15678 (53.1%) had at least one comorbidity. Among 25715 (87.1%) symptomatic patients, fever was the commonest symptom (72.3%) followed by shortness of breath (48.9%) and dry cough (45.5%). In-hospital mortality was 14.5% (n=3957). Adjusted odds of dying were significantly higher in age-group [&ge;]60 years, males, with diabetes, chronic kidney diseases, chronic liver disease, malignancy, and tuberculosis, presenting with dyspnea and neurological symptoms. WHO ordinal scale 4 or above at admission carried the highest odds of dying [5.6 (95% CI: 4.6, 7.0)]. Patients receiving one [OR: 0.5 (95% CI: 0.4, 0.7)] or two doses of anti-SARS CoV-2 vaccine [OR: 0.4 (95% CI: 0.3, 0.7)] were protected from in-hospital mortality. ConclusionsWHO ordinal scale at admission is the most important independent predictor for in-hospital death in COVID-19 patients. Anti-SARS-CoV2 vaccination provides significant protection against mortality.

The coronavirus (COVID-19) is spreading rapidly across the country but Indias testing regime is far from the global standards. It is important to identify the states where testing needs expansion and the magnitudes of active COVID cases are higher focusing on current health infrastructure to meet the pandemic. The data on COVID-19 was extracted from the Application Programming Interface. Test positive rate, test per confirmed case, recovery rate, case fatality rate, and percent distribution of active cases were computed. Availability of hospitals, hospital beds, intensive care unit and ventilators per lakh population was also computed by public and private sector. The result revealed that, Maharashtra constitutes more than one-third positive cases in the country. More than a quarter of the active cases in India belonged to the Mumbai district of Maharashtra, followed by the Chennai district (9.4%) and Ahmedabad district (9.1%). Further, about 40 percent of the active cases in India belonged to the 11 districts of Maharashtra. The increased test positive rate in Maharashtra and Gujarat to almost double in last one month is a concern. In order to bring the states and the country in right track, the test positive rate need to be brought down to below 2 percent. The procurement of higher number of high throughput machine, the Cobas 6800 testing machine, is need of the hour. Only few states have adequate health infrastructure. The priority should be the laid on expansion of more laboratories and hospitals, storage of PPE kit, testing kit, and indigenously developed vaccines. HighlightsO_LIMaharashtra is having the highest number of positive cases followed by Gujarat and Tamil Nadu. Maharashtra constitutes more than one-third positive cases in the country, but the test per confirmed cases (8) is much lower than the other states. C_LIO_LIMore than a quarter of the active cases in India belonged to the Mumbai district (26.1%) of Maharashtra, followed by the Chennai district (9.4%) and Ahmedabad district (9.1%). Further, about 40 percent of the active cases in India belonged to the 11 districts of Maharashtra. C_LIO_LIThe test positive rate is higher in Maharashtra, Gujarat and Delhi is a concern. C_LIO_LIThe recovery rate in India increased substantially by 26.5 percent point from 11.9 percent on April 14 to 38.4 percent on May 17, 2020. C_LIO_LIThe case fatality rate of Covid-19 in India declined by 0.2 percent from 3.4 percent on April 14 to 3.2 percent on May 17 in India. C_LIO_LIThe number of Dedicated Covid Hospitals is not sufficient in India. C_LIO_LIThe available ventilators in the country will deficit in near future to cater to a growing number of active Covid-19 patients and the burden of other communicable and non-communicable diseases. C_LIO_LIIndia has only 569 testing laboratories (396 govt. and 173 private) against its 1.35 billion population. The procurement of higher number of high throughput machine, the Cobas 6800 testing machine, is need of the hour. C_LI

BackgroundSARS-CoV-2 has evolved rapidly, resulting in emergence of lineages with competitive advantage over one another. Co-infections with different SARS-CoV-2 lineages can give rise to recombinant lineages. To date, XBB lineage is the most widespread recombinant lineage worldwide, with the recently named XBB.1.16 lineage causing a surge in the number of COVID-19 cases in India. MethodologyThe present study involved retrieval of SARS-CoV-2 genome sequences from India (between 1st December 2022 and 8th April 2023) through GISAID; sequences were curated, followed by lineage and phylogenetic analysis. Demographic and clinical data from Maharashtra, India were collected telephonically, recorded in Microsoft(R) Excel, and analysed using IBM(R) SPSS statistics, version 29.0.0.0 (241). ResultsA total of 2,944 sequences were downloaded from the GISAID database, of which 2,856 were included in the study following data curation. The sequences from India were dominated by the XBB.1.16* lineage (36.17%) followed by XBB.2.3* (12.11%) and XBB.1.5* (10.36%). Of the 2,856 cases, 693 were from Maharashtra; 386 of these were included in the clinical study. The clinical features of COVID-19 cases with XBB.1.16* infection (XBB.1.16* cases, 276 in number) showed that 92% of those had a symptomatic disease, with fever (67%), cough (42%), rhinorrhoea (33.7%), body ache (14.5%) and fatigue (14.1%) being the most common symptoms. Presence of comorbidity was found in 17.7% of the XBB.1.16* cases. Among the XBB.1.16* cases, 91.7% were vaccinated with at least one dose of vaccine against COVID-19. While 74.3% of XBB.1.16* cases were home-isolated; 25.7% needed hospitalization/institutional quarantine, of these, 33.8% needed oxygen therapy. Out of 276 XBB.1.16* cases, seven (2.5%) cases succumbed to the disease. Majority of XBB.1.16* cases who died belonged to an elderly age group (60 years and above), had underlying comorbid condition/s, and needed supplemental oxygen therapy. The clinical features of COVID-19 cases infected with other co-circulating Omicron variants were similar to XBB.1.16* cases. ConclusionThe study reveals that XBB.1.16* lineage has become the most predominant SARS-CoV-2 lineage in India. The study also shows that the clinical features and outcome of XBB.1.16* cases were similar to those of other co-circulating Omicron lineage infected cases in Maharashtra, India.

BackgroundSeroprevalence of IgG antibodies against SARS-CoV-2 is an important tool to estimate the true extent of infection in a population. However, seroprevalence studies have been scarce in South East Asia including India, which, as of now, carries the third largest burden of confirmed cases in the world. The present study aimed to estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody among hospitalized patients at one of the largest government hospital in India. MethodThis cross-sectional study, conducted at a tertiary care hospital in North India, recruited consecutive patients who were negative for SARS-CoV-2 by RT-PCR or CB-NAAT. Anti-SARS-CoV-2 IgG antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the ELISA method. ResultsA total of 212 hospitalized patients were recruited in the study with mean age ({+/-}SD) of 41.2 ({+/-}15.4) years and 55% male population. Positive serology against SARS CoV-2 was detected in 19.8% patients(95% CI 14.7-25.8). Residency in Delhi conferred a higher frequency of seropositivity 26.5% (95% CI 19.3-34.7) as compared to that of other states 8% (95% CI 3.0-16.4) with p value 0.001. No particular age groups or socio-economic strata showed a higher proportion of seropositivity. ConclusionAround, one-fifth of hospitalized patients, who were not diagnosed with COVID-19 before, demonstrated seropositivity against SARS-CoV-2. While there was no significant difference in the different age groups and socio-economic classes; residence in Delhi was associated with increased risk (relative risk of 3.62, 95% CI 1.59-8.21)

The interaction of adolescent pregnancy with HIV is a complex and crucial public health issue worldwide. This is evident in sub-Saharan Africa, where the co-occurrence of HIV and adolescent pregnancies represents a high risk for additional health and social consequences for both adolescent mothers and their children. This study aims to explore literature to provide a clear synthesis of data related to pregnancies among adolescents living with HIV in Sub-Saharan Africa. A literature search was conducted in July 2023 using PubMed, Scopus, CINAHL, Cochrane Library, African Journals Online, and World Health Organization Global Index Medicus. Two authors screened potential studies. Articles selected were those published in or translated into the English language between 2002 and 2022. Among 1,560 identified results, 25 peer-reviewed publications on pregnancy among adolescents living with HIV in Sub-Saharan Africa were included after screening. The studies, included both qualitative and quantitative data, with a total of 178,227 participants in the age range of 12-18 years. The majority of the studies reported quantitative data, while a few presented qualitative or mixed-methods findings. This scoping review highlights disparities in pregnancy prevalence, revealing varied rates among different age groups. The underrepresentation of adolescents in demographic studies suggests diverse vulnerabilities and access to healthcare. The study also emphasizes the need for tailored healthcare services and comprehensive interventions addressing HIV risk, mental health challenges, and socio-economic barriers.

BackgroundCorona Virus Disease 2019 (COVID-19) caused public emergency with serious morbidity and mortality worldwide between 2020 and 2022, The direct impact of the disease and associated mortality may have been relatively limited in Sub-Saharan Africa (SSA), compared to the impact in other regions. The factors that are considered high risk for acquisition of COVID-19 and associated high mortality rate amongst in-patients are varied in different settings, there are limited data from regional referral designated COVID-19 Treatment Units (CTU) in Uganda. This research assessed the mortality rate, the sub-populations at high risk and characteristics of COVID-19 patients hospitalized in Lira Regional Referral Hospital (LRRH). ObjectiveTo describe COVID-19 characteristic, mortality and associated risk factors among patients admitted at the Lira Regional referral hospital COVID 19 Treatment Unit in northern Uganda. DesignCross Sectional Study with use of Secondary Data SettingThis study was conducted at Lira RRH between January 2023 and December 2023. The data used were for patients admitted from May 2020 to March 2022. ParticipantIn this study all the patients with confirmed COVID-19 were selected by simple census sampling technique, 490 participants were included in the study and these were a) moderately to critically ill patients, b) mild or asymptomatic patients with comorbidity, c) those with positive COVID-19 test and d) those who were admitted in the hospital. ResultsIn the final analysis, 490 participants were considered. Out of this, 251 (52%) were females. Majority 203(41%) were older than 60 years of age. Most of the patients presented with cough 369(89.56%), difficulty in breathing (DIB) 293(78.76%), chest pain 237(69.3%), general body weakness (GBW) 199(63.38%) and fever 179(61.3%). Common pre-existing comorbidities were hypertension 139(29.96%), diabetes mellitus 89(19.47%) and HIV 44(10%). Of all the patients admitted, 187(40%) had severe disease and 34(7%) were critically ill. Overall from May 2020 to March 2022, 142(29%) died. Oxygen saturation (SPO2) 92-100% had 89% decreased mortality (aOR-0.11, 95% CI 0.03-0.44, p-value-0.002). Body temperature 35.5-37.5 degrees Celsius had 78% decreased mortality (aOR-0.22, 95% CI 0.05-0.99, p-value-0.049). Those without Chronic Liver Disease (CLD) had 99% decreased mortality (aOR-0.01, 95% CI 0.001-0.46, p-value-0.017). Age 31-45yrs had 86% decreased mortality (aOR-0.14, 95% CI 0.03-0.74, p-value-0.021) ConclusionThe in-hospital mortality rate in our cohort of COVID 19 patients admitted at LRRH was high. Not having chronic liver disease, normal oxygen saturation, normal body temperature and younger age were associated with decreased likelihood of death.

HIV/AIDS continues to be a global public health problem. Studies of the incidence and prevalence of HIV and other sexually transmitted infections (STIs) that may contribute to or aggravate its acquisition remain an effective means of prevention. In recent years, terrorist groups have established themselves in the northern regions of Cameroon. This insecurity has led to a large influx of refugees with no information about their HIV and STI status. Given this above mentioned situation, this study aimed to assess the incidence and prevalence of HIV and STI and their associated risk factors in order to adjust strategies to monitor the epidemic. A cohort of 684 consenting participants from the North and Far North were enrolled in the study in 2021 and followed up in 2022 to measure the incidence and prevalence of HIV and to assess some associated risk factors. Each participant was administered a pretested questionnaire to collect sociodemographic variables and risk behaviors. Anti-HIV Ab, HBsAg (Hepatitis B Surface Antigen), TPHA (Treponema Pallidum Hemagglutination Assay) tests were performed. The data were compiled using EPI Info 7.5.2 for epidemiological analyses. The association between co-infections of HIV, Hepatitis, and syphilis and HIV incidence was evaluated using the Chi-2 test. The HIV incidence and overall prevalence were 1.63% (163/10,000 population) and 3.8%, respectively. The HIV incidence increased from 0.27% in 2017 (DHS) to 1.63% in the North and Far North regions as found in our study. The incidences of syphilis and hepatitis B were 1.03% and 4.56%, respectively. Factors associated with HIV acquisition included religion (Muslims being more infected, P<0.03), unprotected sex with a new partner (P<0.007), having a sex worker as a partner (P<0.0001), and co-infection with syphilis and hepatitis B (P<0.05). The findings also link increased HIV incidence to insecurity and population displacement. In HIV prevention strategies, it is important to consider the security and political stability context as well as HIV-associated infections such as hepatitis B and syphilis.

BackgroundThe ongoing pandemic of Corona virus disease 2019(covid-19) is caused by severe acute respiratory syndrome Corona virus 2(SAR-COV-2). The world health organization declared it as public health emergency of international concern on January 2020, and later declared as pandemic on 11 March 2020.One of the high-risk groups for COVID-19 disease are people residing in urban overcrowded slums and as most of the population is migrant, they are less aware of the pandemic and have less access to health care facilities. Vaccinating these high-risk groups can decrease disease burden and control the ongoing pandemic. Objectives1] To estimate COVID 19 vaccination coverage 2] To assess the factors responsible for COVID - 19 vaccination coverage and vaccine hesitancy 3] To study AEFI pattern following COVID-19 vaccination 4] To determine the prevalence of breakthrough infections after COVID - 19 Vaccination in urban slums of Bengaluru, India. MethodologyA community based cross sectional study was conducted in Urban slums belonging to Urban Health and Training Centre, Department of community medicine, Akash Institute of Medical Sciences and Research Centre, Bengaluru Rural District, Karnataka, India. After obtaining Institutional ethical clearance and informed consent from study participants, data was collected from 1638 participants, fulfilling inclusion criteria using a predesigned, pretested, structured questionnaire. Data was entered in Microsoft excel and analyzed using SPSS version 24. Chi square test and Fischers exact test was applied and p <0.05 considered as statistically significant. ResultsIn the present study, 35.5% (583 out of 1638) of the study participants had taken COVID Vaccine, of which 533 (91.42%) were partially vaccinated and remaining 50 (8.5%) were fully Vaccinated. Majority i.e., 98.45% have taken vaccine at Govt health centers. 63.65% vaccinated with Covishield reported adverse events, whereas 18.6% vaccinated with Covaxin reported adverse events. Adverse events were more likely to be reported by women (74.7%) compared to men (58.6%), this observation was consistent across all age groups. Vaccination coverage was high among 18 - 45 years age group (37.75%), males (64.86%), Christians (47.05%) followed by Hindus (43.56%), graduates (95.67%), clerical and skilled workers (70.75%), Upper middle socioeconomic class (72.41%). This difference was statistically significant. Our study reported Break through infections in 7 out of total 583 vaccinated with a prevalence of 1.2%. The break through infections was very high among partially vaccinated (85.71%) as compared to fully vaccinated individuals (14.28%). This was observed among those vaccinated with Covaxin only. ConclusionThe COVID vaccine coverage was low in urban slums. The prevalence of Break through infections in our study was higher as compared to available data/reports in the country. Break through infections was very high among partially vaccinated as compared to fully vaccinated individuals. This study on break through infections on COVID vaccination is first study in South India on general population. The most important factor for vaccine hesitancy is the occurrence of mild or serious adverse effects following immunization, and this may be the biggest challenge in the global response against the pandemic.

BackgroundSeroprevalence of IgG antibodies against SARS-CoV-2 is an important tool to estimate true burden of infection in a given population. Serosurveys, though being conducted in different parts of India, are not readily published in entirety and often do not report on the different characteristics of the population studied. In this present study, we aimed to serially estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody over 11 months at one of the largest government hospital in India. MethodIn this cross-sectional study which was conducted between between 9th June 2020 and 27th April 2021, consecutive patients admitted to medicine wards or intensive care units, who were negative for SARS-CoV-2 by RT-PCR or CBNAAT were included. The 2linic-demographic features of the subjects were recorded in pre-formed questionnaires. Anti-SARS-CoV2 antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the ELISA method. ResultsA total of 916 patients were recruited over 11 months with mean age({+/-}SD) 39.79{+/-}14.9 of years and 55% of population being males. In total 264(28.8%) patients were found to be seropositive. Residency in Delhi and non-smoking status conferred a higher risk for seropositivity. The adjusted odds ratio for seropositivity with regards to no smoking and residence out of Delhi were .31{+/-}.09 (Odds ratio {+/-} S.E) and .65 {+/-} .1 (Odds ratio {+/-} S.E) respectively. No other factors like age, socio-economic status, contact history etc showed significant relationship with seropositivity. ConclusionThe seropositivity rate among hospitalized patients was found to increase with time (from 8.45% to 38%) over a period of 9 months. Residence in Delhi and non-smokers had higher risk for seropositivity on multivariate analysis.

ObjectiveThe objective of this study is to evaluate the association with different factors empirically found to affect the spread and the severity of Covid-19. Evidently there is less likelihood of having one single and absolute solution to this pandemic. It is pragmatic to look for a multi-pronged and collaborative assembly of probable solutions, which is the higher objective of this study. DesignEcological study. SettingGlobal setting including 45 countries from all six inhabited continents PopulationTwo (2) or three (3) countries from each geographical region of the continents selected on the basis of population Main outcomemeasures correlation factors derived from comparisons between different sets of variables ResultsEmpirical trends suggested in the existing literature were quantified in a global setting establishing clear trends. Correlation between the proportion of the population affected and median age, prime climate zones, malaria and tuberculosis incidence, BCG coverage and mitigation measures were established. ConclusionsThe study findings suggest that demographic and climatological factors, high endemicity of TB and Malaria, and universal BCG programmes may have a cushioning effect in the impact of Covid-19 on health systems of poorer and developing nations. In the light of these findings more emphasis is necessary on the protective effects of BCG and antiviral properties of antimalarial drugs. BackgroundThe coronavirus disease (Covid-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected 213 countries as of 20th May 2020, with a total of 5,017,883 total cases reported globally, and has caused 325,624 reported deaths till date (worldometers.info). It began with the report of an outbreak of pneumonia of unknown cause in Wuhan, China on 31st December 2019. This outbreak was declared a Public Health Emergency of International Concern on 30th January 2020. Even as early as 18th February 2020, it was noted that inspite of lower case fatality rates Covid-19 had already resulted in more deaths than SARS and MERS combined.1 On the 11th of March the WHO made the assessment that Covid-19 could be classified as a pandemic. A systematic review found the basic reproduction number between 2.0 - 3.0.2 According to the WHO, the crude case fatality rate is 3%, with 15% of those affected suffering from severe disease and 5% critical.3 As developed countries with highly ranked health systems report high burden of cases straining health system capacities, concerns grow about the impact on resource constrained health systems in developing and underdeveloped nations. A better understanding of the disease epidemiology could help in planning the pandemic response, both in terms of resource allocation and mitigation measures in areas and populations more likely to be affected. In the second week of April, 2020, the IMF also was reported to be keen to know the reason behind the lower impact of Covid-19 in African and Asian countries; this also served as a driving factor behind this study.