Epidemiology of Coronavirus Disease 2019 during the Second and Third Wave in Chennai, India: An Analysis of the Coronavirus Disease 2019 Surveillance System, February 2021-February 2022.

INTRODUCTION: Analysis of the coronavirus disease 2019 (COVID-19) surveillance system in the first wave indicated that the data-driven approach helped in resource allocation and public health interventions. OBJECTIVES: We described the epidemiology of COVID-19 cases in Chennai, Tamil Nadu, India, from February 2021 to February 2022. MATERIALS AND METHODS: We analyzed the COVID-19 surveillance data from Chennai City, Tamil Nadu, India's Greater Chennai Corporation. We described the deidentified line list of COVID-19 cases and deaths by months, zones, age, and gender. We estimated the incidence of COVID-19 cases per million population, test positivity rate (TPR), and case fatality ratio (CFR). RESULTS: Of the 434,040 cases reported in Chennai from February 1, 2021, to February 28, 2022, 53% were male. The incidence per million peaked in May 2021 (19,210) and January 2022 (15,881). Age groups more than 60 years reported maximum incidence. Southern region zones reported higher incidence. Overall TPR was 5.8%, peaked in May 2021 (17.5%) and January 2022 (15.1%). Over half of the 4929 reported deaths were in May 2021 (56%). Almost half of the deaths were 61-80 years (52%), followed by 41-60 years (26%). Overall CFR was 1%, which peaked in June 2021 (4%). CONCLUSION: We conclude that Chennai city experienced a surge in COVID-19 due to delta and omicron variants. Understanding descriptive epidemiology is vital for planning the public health response, resource allocation, vaccination policies, and risk communication to the community.

Face mask use in the city of Chennai, India: Results from three serial cross-sectional surveys, 2021.

INTRODUCTION: The Government of Tamil Nadu, India, mandated wearing face masks in public places to combat the COVID-19 pandemic. We established face mask surveillance and estimated the prevalence of appropriate mask use (covering the nose, mouth, and chin) in the slums and non-slums of Chennai at different time points in 2021. METHODS: We conducted three serial cross-sectional surveys in the outdoors and indoors of Chennai in March, July, and October 2021. We observed the mask wearing among 3200 individuals in the outdoors and 1280 in the indoors. We divided the outdoor and indoor locations into slums and non-slums. In October 2021, we also surveyed 150 individuals from each of the 11 shopping malls in the city. We calculated the proportions and 95% confidence interval (95%CI) for the appropriate mask use in the outdoor, indoor, and malls by age, gender, region, and setting (slum and non-slum). RESULTS: We observed 3200 individuals in the outdoor and 1280 individuals in the indoor setting, each from a slum and non-slum, during the three rounds of the study. In outdoor and indoors, males comprised three-fourths and middle-aged individuals were half the study population. Mask compliance changed significantly with time (p-value <0.001). Males consistently demonstrated better compliance in all rounds. The south region had the highest mask compliance in slums indoors and outdoors in rounds 4 and 5. Young adults had the highest mask compliance in both outdoor slums and non-slums in all rounds. Overall mask compliance in shopping malls was 57% (95% CI: 48-65). CONCLUSION: The mask compliance in Chennai outdoors during the COVID-19 pandemic was less than 50%, with variations across time points by gender, age groups, and geographical locations. We must develop more effective communication strategies for older age groups and crowded indoor settings.

Resurgence of Diphtheria in North Kerala, India, 2016: Laboratory Supported Case-Based Surveillance Outcomes.

INTRODUCTION: As part of national program, laboratory supported vaccine preventable diseases surveillance was initiated in Kerala in 2015. Mechanisms have been strengthened for case investigation, reporting, and data management. Specimens collected and sent to state and reference laboratories for confirmation and molecular surveillance. The major objective of this study is to understand the epidemiological information generated through surveillance system and its utilization for action. METHODS: Surveillance data captured from reporting register, case investigation forms, and laboratory reports was analyzed. Cases were allotted unique ID and no personal identifying information was used for analysis. Throat swabs were collected from investigated cases as part of surveillance system. All Corynebacterium diphtheriae isolates were confirmed with standard biochemical tests, ELEK's test, and real-time PCR. Isolates were characterized using whole genome-based multi locus sequence typing method. Case investigation forms and laboratory results were recorded electronically. Public health response by government was also reviewed. RESULTS: A total of 533 cases were identified in 11 districts of Kerala in 2016, of which 92% occurred in 3 districts of north Kerala; Malappuram, Kozhikode, and Kannur. Almost 79% cases occurred in >10 years age group. In <18 years age group, 62% were male while in ≥18 years, 69% were females. In <10 years age group, 31% children had received three doses of diphtheria vaccine, whereas in ≥10 years, 3% cases had received all doses. Fifteen toxigenic C. diphtheriae isolates represented 6 novel sequence types (STs) (ST-405, ST-408, ST-466, ST-468, ST-469, and ST-470). Other STs observed are ST-50, ST-295, and ST-377. CONCLUSION: Diphtheria being an emerging pathogen, establishing quality surveillance for providing real-time information on disease occurrence and mortality is imperative. The epidemiological data thus generated was used for targeted interventions and to formulate vaccine policies. The data on molecular surveillance have given an insight on strain variation and transmission patterns.