IJID Regions

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.

A population-representative serological study was conducted in all districts of the state of Tamil Nadu (population 72 million), India, in October-November 2020. State-level seroprevalence was 31.6%. However, this masks substantial variation across the state. Seroprevalence ranged from just 11.1% in The Nilgris to 51.0% in Perambalur district. Seroprevalence in urban areas (36.9%) was higher than in rural areas (26.9%). Females (30.8%) had similar seroprevalence to males (30.3%). However, working age populations (age 40-49: 31.6%) have significantly higher seroprevalence than the youth (age 18-29: 30.7%) or elderly (age 70+: 25.8%). Estimated seroprevalence implies that at least 22.6 million persons were infected by the end of November, roughly 36 times the number of confirmed cases. Estimated seroprevalence implies an infection fatality rate of 0.052%.

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

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

Background: In this report, we describe the epidemiology of SARS-CoV-2 infection, specifically examining how the symptomatic persons drove the transmission in the state of Karnataka, India, during the lockdown phase. Methods: The study included all the cases reported from March 8 to May 31, 2020 in the state. Any person with history of international or domestic travel from high burden states, those presenting with Influenza-like or Severe Acute Respiratory Illness and high-risk contacts of COVID19 cases, who were SARS-CoV-2 RT-PCR positive were included. Detailed analysis based on contact tracing data available from line-list of the state surveillance unit was performed using cluster analysis software package. Findings: Amongst the 3404 COVID-19 positive cases, 3096 (91%) were asymptomatic while 308 (9%) were symptomatic. Majority of the asymptomatic cases were in the age range of 16-50 years while symptomatic cases were between 31-65 years. Most of those affected were males. Cluster analysis of 822 cases indicated that the secondary attack rate, size of the cluster (dispersion) and occurrence of overt clinical illness is significantly higher when the index case in a cluster was symptomatic compared to an asymptomatic. Interpretation: Our findings indicate that both asymptomatic and symptomatic SARS-CoV-2 cases transmit the infection; however, the main driving force behind the spread of infection within the state was significantly higher from symptomatic cases. This has major implications for policies related to testing. Active search for symptomatic cases, subjecting them to testing and treatment should be prioritized for containing the spread of COVID-19.

BackgroundSARS-CoV-2 infection has caused 64,469 deaths in India, with 7, 81, 975 active cases till 30th August 2020, lifting it to 3rd rank globally. To estimate the burden of the disease with time it is important to undertake a longitudinal seroprevalence study which will also help to understand the stability of anti SARS-CoV-2 antibodies. Various studies have been conducted worldwide to assess the antibody stability. However, there is very limited data available from India. Healthcare workers (HCW) are the frontline workforce and more exposed to the COVID-19 infection (SARS-CoV-2) compared to the community. This study was conceptualized with an aim to estimate the seroprevalence in hospital and general population and determine the stability of anti SARS-CoV-2 antibodies in HCW. MethodsStaff of a tertiary care hospital in Delhi and individuals visiting that hospital were recruited between April to August 2020. Venous blood sample, demographic, clinical, COVID-19 symptoms, and RT-PCR data was collected from all participants. Serological testing was performed using the electro-chemiluminescence based assay developed by Roche Diagnostics, in Cobas Elecsys 411. Seropositive participants were followed- upto 83 days to check for the presence of antibodies. ResultsA total of 780 participants were included in this study, which comprised 448 HCW and 332 individuals from the general population. Among the HCW, seroprevalence rates increased from 2.3% in April to 50.6% in July. The cumulative prevalence was 16.5% in HCW and 23.5% (78/332) in the general population with a large number of asymptomatic individuals. Out of 74 seropositive HCWs, 51 were followed-up for the duration of this study. We observed that in all seropositive cases the antibodies were sustained even up to 83 days. ConclusionThe cumulative prevalence of seropositivity was lower in HCWs than the general population. There were a large number of asymptomatic cases and the antibodies developed persisted through the duration of the study. More such longitudinal serology studies are needed to better understand the antibody response kinetics.

Serial household antibody sero-surveys informs the pandemic where testing is non-uniform. Young populations with intergenerational co-residence may have different transmission dynamics. We conducted two serial cross-sectional surveys in April and June 2020 in low- and high-transmission neighborhoods of Karachi, Pakistan, using random sampling. Symptoms were assessed and blood tested for antibody using chemiluminescence. Seroprevalence was adjusted using Bayesian regression and post stratification. CRI with 95% confidence intervals was obtained. We enrolled 2004 participants from 406 households. In June 8.7% (95% CI 5.1-13.1) and 15.1% (95% CI 9.4-21.7) were infected in low- and high-transmission-areas respectively compared with 0.2% (95% CI 0-0.7) and 0.4% (95% CI 0-1.3) in April. Conditional risk of infection was 0.31 (95% CI 0.16-0.47) and 0.41(95% CI 0.28-0.52) respectively with only 5.4% symptomatic. Rapid increase in seroprevalence from baseline is seen in Karachi, with a high probability of infection within household. Article Summary LineRapid increase in seroprevalence of antibodies against SARS-CoV-2 was seen in Karachi, Pakistan from April to June 2020 with a high conditional risk of infection within the household

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.

Objectives: Current retrospective study aims to evaluate household Secondary Attack Rate (SAR) of COVID-19 in Gandhinagar (rural) district of Gujarat, India. Methods: Line-listing of 486 laboratory-confirmed patients, tested between 28th March to 2nd July was collected, out of them 80 (15% of overall sample) cases were randomly selected. Demographic, clinical and household details of cases were collected through telephonic interview. During interview 28 more patients were identified from the same household and were added accordingly. So, study included 74 unrelated cluster of households with 74 primary cases and 386 close contacts. Results: SAR in household contacts of COVID-19 in Gandhinagar was 8.8%. Out of 108, 8 patients expired (7.4%), where higher mortality was observed in primary cases (9.5%) as compared to secondary cases (3%). Occupational analysis showed that majority of the secondary cases (88%) were not working and hence had higher contact time with patient. No out-of-pocket expenditure occurred in 94% of the patients, in remaining 6% average expenditure of 1,49,633INR (2027 USD) was recorded. Conclusions: Key observations from the study are 1) SAR of 8.8% is relatively low and hence home isolation of the cases can be continued 2) Primary case is more susceptible to fatal outcome as compared to secondary cases 3) Government has covered huge population of the COVID-19 patients under cost protection. However, more robust studies with larger datasets are needed to further validate the findings.

Although the vast majority of confirmed cases of COVID-19 are in low- and middle-income countries, there are relatively few published studies on the epidemiology of SARS-CoV-2 in these countries. The few there are focus on disease prevalence in urban areas. We conducted state-wide surveillance for COVID-19, in both rural and urban areas of Karnataka between June 15-August 29, 2020. We tested for both viral RNA and antibodies targeting the receptor binding domain (RBD). Adjusted seroprevalence across Karnataka was 46.7% (95% CI: 43.3-50.0), including 44.1% (95% CI: 40.0-48.2) in rural and 53.8% (95% CI: 48.4-59.2) in urban areas. The proportion of those testing positive on RT-PCR, ranged from 1.5 to 7.7% in rural areas and 4.0 to 10.5% in urban areas, suggesting a rapidly growing epidemic. The relatively high prevalence in rural areas is consistent with the higher level of mobility measured in rural areas, perhaps because of agricultural activity. Overall seroprevalence in the state implies that by August at least 31.5 million residents had been infected by August, nearly an order of magnitude larger than confirmed cases.

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)

BackgroundSince its first report on March 08, COVID-19 positive cases and number of deaths are increasing in Bangladesh. In the first month of COVID-19 infection, incidence of daily positive cases did follow the susceptible, infected and recovered (SIR) based predictions we reported in April, but started to deviate in the following months. COVID-19 transmission and disease progression depends on multifaceted determinants e.g. viral genetics, host immunity, social distancing, co-morbidity, socio-demographic and environmental parameters. Therefore deviation in confirmed cases from predicted model may appear and warrant thorough investigation. MethodsIn this short report, we compared real data with SIR model and analyzed the possible factors associated with the deviation which included preventive intervention strategies, socioeconomic capabilities, climatic and meteorological indexes, acquired immunity of Bangladeshi population, demographic characteristics, health indicators and food habits. ResultsThe key factor responsible for the observed deviation was found to be the number of tests performed. Having population with low median age, young age groups are being mostly infected. Low prevalence of non-communicable diseases among them and strong immunity compared to the elderly might have kept most of them asymptomatic with silent recovery. Warm temperature, humidity and UV index of Bangladesh during this summer period might have contributed to the slow progression of infection. Longer daylight mediated immunity, fresh air circulations and ventilation, less population density in rural areas and certain food habits perhaps helped the large number of populations to restrict the infection up to a level. ConclusionDespite all these helpful determinants in Bangladesh, person to person contact is still the leading risk factor for COVID-19 transmission. Infection may increase rapidly if safe distance and preventive measures are not strictly followed while resuming the normal social and work life. Expanding test capacity, strong collaborative action plans, strategies and implementation are needed immediately to prevent catastrophe. HighlightsO_LILimited number of tests compared to large population was the key reason for possible low daily positive cases reported in Bangladesh. C_LIO_LIControlled interventions viz. official leave; transport ban and social distancing had helped initially to slow down the transmission. C_LIO_LIWarm weather, high humidity and UV index, sunlight mediated immunity, fresh air circulations, low pollutions, food habit and heterologous immunity might have reduced the transmission capabilities of SARS-CoV-2. C_LIO_LIHaving large number of young people with strong immunity might have kept most of the infected asymptomatic who recovered silently. C_LIO_LIPerson to person contact still remain as key risk factor in COVID-19 transmission, so strict health measures should be in place even after reopening social activities to contain further transmission. C_LI

From the beginning of the pandemic in Feb 2020, Malaysia has been through 4 waves of outbreak, the magnitude of each wave is several orders larger than the preceding one. By the end of the fourth wave in October 2021, Malaysia has among the highest death toll in Asia, cumulative incidence of confirmed cases has reached 7.0% (>30% in Klang Valley). However it remains uncertain what is the true proportion of the population infected. We conducted a sero-survey on 1078 workers from 17 worksites in Klang Valley and Perak between July and September 2021. We tested them for SARS-CoV-2-specific antibodies using Ecotest, a lateral flow immunoassay (LFIA). The ability of antibody testing to detect prior infection depends on the assay and sero-reversion. We therefore adjusted the prevalence estimates to correct for potential misclassification bias due to the use of LFIA and sero-reversion using test sensitivity and specificity results estimated from an independent validation study. The mean age of the workers was 32 years, 89% were male and migrant workers comprised 81% of all subjects, 59% the subjects were from Klang valley. 33% of workers had prior RT-PCR confirmed Covid-19 infections. We estimated 82.2 percent of workers had been infected by Covid-19 by July-September 2021. Prevalence was 99.9% among migrant workers and 12.1% among local workers. Klang Valley, the most industrialized region in Malaysia where most migrant workers are found, had 100% prevalence, giving an infection-to-case ratio (ICF) of [~]3. Our sero-prevalence results show that the incidence of Covid19 is extremely high among migrant workers in Malaysia, consistent with findings from other countries such as Kuwait and Singapore which also hosted large number of migrant workers.

Human Metapneumovirus (hMPV) is a paramyxovirus that was detected in India first in 2004. It causes a mild common cold in most cases but serious illness has been reported in some young children, adults >65 years and the immunocompromised. AIMTo study the age related prevalence of IgG antibodies in the population and also to determine the percent positivity and seasonal variation of hMPV infection. MATERIAL AND METHODSThis cross-sectional study assessed seroprevalence by testing 820 serum samples collected between January 25th - 31st 2025 for hMPV IgG antibodies by ELISA and stratified according to age and sex. hMPV PCR trends: Retrospective data from the 1276 tests for Respiratory Viruses done at our centre during 2023 and 2024 were analysed and comprised of age groups 0-18, 19-30 ,31-45, 45-60 and > 60 years. The relationship between gender (M/F) and outcome (positive/negative) across various age groups was analysed using the chi-square test for independence in Graph Pad Prism 8.0. RESULTS: Seroprevalence studyOverall hMPV IgG Antibody Positivity was 53.4%. Antibody positivity was higher in above 60 years when compared to other groups and was statistically significant (P=0.0001) and female predominance is seen. In hMPV PCR trendsA higher percentage of positivity were observed in > 60years individuals who had hospitalisation when compared to the other groups which was statistically significant(P=0.0001). Overall Percent positivity was 7.8% in 2023 and 3.8% in 2024. Seasonal peaks occurred in Feb-Mar and Oct. 92.6% of patients were discharged and doing well on follow-up and only 7.4% deaths were seen. CONCLUSIONOur findings highlight around 53.4% of the total study population had hMPV IgG antibodies. PCR positivity and antibody positivity was higher in individuals over 60 who had other comorbidities. Hospitalization and mortality rates are significantly high in this high risk groups. Vaccine development for high-risk individuals is recommended.

Four rounds of serological surveys were conducted, spanning two COVID waves (October 2020 and April-May 2021), in Tamil Nadu (population 72 million) state in India. Each round included representative populations in each district of the state, totaling [≥]20,000 persons per round. State-level seroprevalence was 31.5% in round 1 (October-November 2020), after Indias first COVID wave. Seroprevalence fell to 22.9% in 2 (April 2021), consistent with waning of antibodies from natural infection. Seroprevalence rose to 67.1% by round 3 (June-July 2021), reflecting infections from the Delta-variant induced second COVID wave. Seroprevalence rose to 93.1% by round 4 (December 2021-January 2022), reflecting higher vaccination rates. Antibodies also appear to wane after vaccination. Seroprevalence in urban areas was higher than in rural areas, but the gap shrunk over time (35.7 v. 25.7% in round 1, 89.8% v. 91.4% in round 4) as the epidemic spread even in low-density rural areas. Article Summary LineAntibodies waned after Indias first COVID wave and both vaccination and infection contributed its roughly 90% seroprevalence after its second wave.

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.

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.

BackgroundCovid-19 disease is pandemic in more than 85% of the countries in the world, with about 10 million cases and 0.5 million deaths as on July 2, 2020. In India reporting of the first case was on January 30, 2020, and to prevent rapid community spread of the disease nationwide lockdown phase was imposed from March 25- June 1, 2020. Our objective was to assess various epidemiological measures during the lockdown phase. MethodsWe used daily reporting of confirmed cases by the Ministry of Health and Family Welfare, Government of India during the period March 19-June 1, 2020. Using statistical packages STATA and R-packages, we fitted three statistical distributions (Gamma, Weibull and Log-normal) to the daily recorded new cases. We estimated daily incidence rate and death rate per million population, generation time and Basic Reproduction numbers. ResultsDuring the lockdown phase, the daily per cent increase in the cumulative number of cases showed negative exponential growth with 0.022 as an instantaneous rate of decrease. The average incidence rate with a 95% confidence interval (CI) was 1.84 (1.43-2.25). Day specific incidence rate per million (revealed the exponential pattern with 0.069 as the instantaneous rate of increase per day, which accounted for the doubling time of the disease (10 days; 95% CI: 9.25-10.93). Case fatality rate (2.92%; 95% CI: 2.82% -3.02%) and overall death rate was 1.14 (95% CI: 0.87-1.41) per million. were abysmally low. Statistical distribution fitting of new cases found to be satisfactory with Gamma distribution. Basic reproduction numbers 1.83 (95% CI: 1.82-1.83) was less. ConclusionIn India, with a population density of about 450 per Km2, the virulent of COVID-19 transmission was interrupted significantly with 70 days lockdown during the early transmission stage. We observed a considerable decline in all the epidemiological indices compared to the corresponding indices recorded during the same period in the severely affected countries.

Hydrocephalus is routinely treated by surgical procedures. Cerebrospinal fluid shunt placement is a critical therapeutic intervention for hydrocephalus.CSF shunting has multiple complications among which infection is very common. The major cause of morbidity and mortality in patients with CSF shunts is theinfection of the central nervous system (CNS).It can lead to prolonged hospital stay, increase the number of operative procedures 03 times more than then none infected cases and has twice the fatality rate. Study of such type of complication will help the patients to improve their health and also improve our sterilization techniques and reduce burden of hospital and patients expenditures. The objective of the study was to determine the frequency of infection after cerebrospinal fluid shunting procedures.Case series study was used as study design.Study was conducted from 10-2010 to 10-06-2011.One hundred and forty four patients with both genders of all age groups undergoing cerebrospinal fluid shunting, meeting inclusion and exclusion criteria, were selected for the present study after informed consent of patient or guardian and approval by the hospital ethical committee. Follow up was ensured by taking the telephonic contact and address of patient.Total no of patients were 144 among which, 89 were males and 55 were females. Age distribution was from 01 month to 75 years with the mean age of 15.280 and standard deviation was {+/-} 20.450. Post-operative infection was present in 20(13.9%) patients. Authors approvalAll the authors have seen the manuscript and approved it. Declaration of interestNone Conflict/Competing of InterestNone. Disclosure of FundingNone. Ethical ApprovalAttached

Background: Georgia timely implemented effective response measures, with testing, contact tracing and isolation being the main pillar of the national response, achieving the lowest cumulative incidence of SARS-CoV-2 in the European region. Methods: We conducted a survey to estimate SARS-CoV-2 IgG antibody seroprevalence among adult residents of capital city of Tbilisi (adult population: 859,328). Participants were recruited through respondent driven sampling during May 18-27, 2020. Blood specimens were tested for SARS-CoV-2 IgG antibodies using commercially available lateral flow immunoassay (COVID-19 IgG/IgM Rapid Test Cassette, Zhejiang Orient Gene Biotech). Crude seroprevalence was weighted by population characteristics (age, sex, district of Tbilisi) and further adjusted for test accuracy. Results: Among 1,068 adults recruited 963 (90.2%) were between 18 and 64 years-old, 682 (63.9%) women. 176 (16.5%) reported symptoms indicative of SARS-CoV-2 infection occurring in previous three months. Nine persons tested positive for IgG: crude seroprevalence: 0.84%, (95% CI: 0.33%-1.59%), weighted seroprevalence: 0.94% (95% CI: 0.37%-1.95%), weighted and adjusted for test accuracy: 1.02% (95% CI: 0.38%-2.18%). The seroprevalence estimates translate into 7,200 to 8,800 infections among adult residents of Tbilisi, which is at least 20 times higher than the number of confirmed cases. Conclusions: Low seroprevalence confirms that Georgia successfully contained spread of SARS-CoV-2 during the first wave of pandemic. Findings also suggest that undocumented cases due to asymptomatic or very mild disease account for majority of infections. Given that asymptomatic persons can potentially spread the virus, test and isolate approach should be further expanded to control the epidemic.