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.

Experiences, Challenges, and Lessons Learned During Implementation of a Remote Monitoring Program for Home-Isolated COVID-19 Patients in Chennai, India.

During the early months of the COVID-19 pandemic in 2020, the majority of the identified COVID-19 patients in Chennai, a southern metropolitan city of India, presented as asymptomatic or with mild clinical illness. Providing facility-based care for these patients was not feasible in an overburdened health system. Thus, providing home-based clinical care for patients who were asymptomatic or with mild clinical illnesses was a viable solution. Because of the imminent possibility of worsening clinical conditions in home-isolated COVID-19 patients, continuous monitoring for red flag signs was essential. With growing evidence of the effectiveness of remote monitoring of patients, the Greater Chennai Corporation in partnership with the National Institute of Epidemiology conceptualized and implemented a remote monitoring program for home-isolated COVID-19 patients. The key steps used to develop the program were to (1) decentralize triage systems and establish a home-isolation protocol, (2) develop a remote monitoring platform and remote health care workforce, and (3) onboard patients and conduct remote hybrid monitoring. In this article, we share the pragmatic solutions, critical components of the systems and processes, lessons, and experiences in implementing a remote monitoring program for home-isolated COVID-19 patients in a large metropolitan setting.