Trends in Influenza Infections in Three States of India from 2015-2021: Has There Been a Change during COVID-19 Pandemic?

The COVID-19 pandemic and public health response to the pandemic has caused huge setbacks in the management of other infectious diseases. In the present study, we aimed to (i) assess the trends in numbers of samples from patients with influenza-like illness and severe acute respiratory syndrome tested for influenza and the number and proportion of cases detected from 2015-2021 and (ii) examine if there were changes during the COVID-19 period (2020-2021) compared to the pre-COVID-19 period (2015-2019) in three states of India. The median (IQR) number of samples tested per month during the pre-COVID-19 period was 653 (395-1245), compared to 27 (11-98) during the COVID-19 period (p value < 0.001). The median (IQR) number of influenza cases detected per month during the pre-COVID-19 period was 190 (113-372), compared to 29 (27-30) during the COVID-19 period (p value < 0.001). Interrupted time series analysis (adjusting for seasonality and testing charges) confirmed a significant reduction in the total number of samples tested and influenza cases detected during the COVID-19 period. However, there was no change in the influenza positivity rate between pre-COVID-19 (29%) and COVID-19 (30%) period. These findings suggest that COVID-19-related disruptions, poor health-seeking behavior, and overburdened health systems might have led to a reduction in reported influenza cases rather than a true reduction in disease transmission.

Severe acute respiratory illness surveillance for influenza in Kenya: Patient characteristics and lessons learnt.

BACKGROUND: We describe the epidemiology and clinical features of Kenyan patients hospitalized with laboratory-confirmed influenza compared with those testing negative and discuss the potential contribution of severe acute respiratory illness (SARI) surveillance in monitoring a broader range of respiratory pathogens. METHODS: We described demographic and clinical characteristics of SARI cases among children (<18 years) and adults, separately. We compared disease severity (clinical features and treatment) of hospitalized influenza positive versus negative cases and explored independent predictors of death among SARI cases using a multivariable logistic regression model. RESULTS: From January 2014 to December 2018, 11,166 persons were hospitalized with SARI and overall positivity for influenza was ~10%. There were 10,742 (96%) children (<18 years)-median age of 1 year, interquartile range (IQR = 6 months, 2 years). Only 424 (4%) of the SARI cases were adults (≥18 years), with median age of 38 years (IQR 28 years, 52 years). There was no difference in disease severity comparing influenza positive and negative cases among children. Children hospitalized with SARI who had an underlying illness had greater odds of in-hospital death compared with those without (adjusted odds ratio 2.11 95% CI 1.09-4.07). No further analysis was done among adults due to the small sample size. CONCLUSION: Kenya's sentinel surveillance for SARI mainly captures data on younger children. Hospital-based platforms designed to monitor influenza viruses and associated disease burden may be adapted and expanded to other respiratory viruses to inform public health interventions. Efforts should be made to capture adults as part of routine respiratory surveillance.

Performance of the Severe Acute Respiratory Illness Sentinel Surveillance System in Yemen: Mixed Methods Evaluation Study.

BACKGROUND: The national severe acute respiratory illness (SARI) surveillance system in Yemen was established in 2010 to monitor SARI occurrence in humans and provide a foundation for detecting SARI outbreaks. OBJECTIVE: To ensure that the objectives of national surveillance are being met, this study aimed to examine the level of usefulness and the performance of the SARI surveillance system in Yemen. METHODS: The updated Centers for Disease Control and Prevention guidelines were used for the purposes of our evaluation. Related documents and reports were reviewed. Data were collected from 4 central-level managers and stakeholders and from 10 focal points at 4 sentinel sites by using a semistructured questionnaire. For each attribute, percent scores were calculated and ranked as follows: very poor (≤20%), poor (20%-40%), average (40%-60%), good (60%-80%), and excellent (>80%). RESULTS: As rated by the evaluators, the SARI surveillance system achieved its objectives. The system's flexibility (percent score: 86%) and acceptability (percent score: 82%) were rated as "excellent," and simplicity (percent score: 74%) and stability (percent score: 75%) were rated as "good." The percent score for timeliness was 23% in 2018, which indicated poor timeliness. The overall data quality percent score of the SARI system was 98.5%. Despite its many strengths, the SARI system has some weaknesses. For example, it depends on irregular external financial support. CONCLUSIONS: The SARI surveillance system was useful in estimating morbidity and mortality, monitoring the trends of the disease, and promoting research for informing prevention and control measures. The overall performance of the SARI surveillance system was good. We recommend expanding the system by promoting private health facilities' (eg, private hospitals and private health centers) engagement in SARI surveillance, establishing an electronic database at central and peripheral sites, and providing the National Central Public Health Laboratory with the reagents needed for disease confirmation.

Epidemiological determinants of COVID-19 infection and mortality: A study among patients presenting with severe acute respiratory illness during the pandemic in Bihar, India.

OBJECTIVES: The study was designed to explore epidemiological characteristics, determinants of COVID-19 infection development and mortality of patients presenting with severe acute respiratory illness (SARI) to a tertiary care health facility of Bihar. METHODS: This was an observational record-based study, longitudinal in design. Data of 281 SARI patients who have attended All India Institute of Medical Sciences, Patna, Bihar, India during 25th April 2020, till 12th July 2020 (16 weeks) were used for the study. RESULTS: Out of 281 study participants, 95 (33.8%) were detected to have COVID-19 and 42 (14.9%) died. Among COVID-positive study subject's death rate was 28.4%. In the multivariable logistic regression analysis; increasing age (adjusted odds ratio [AOR] = 1.02 [1.00-1.03]), gender (males) (AOR = 2.51 [1.27-4.96]), presenting symptom (cough) (AOR = 2.88 [1.46-5.70]), co-morbidity (hypothyroidism) (AOR = 4.59 [1.45-14.56]) and delay between symptom onset and admission (>2 days) (AOR = 2.46 [1.19-5.07]) were significant predictors of COVID-19 infection among study participants adjusted with other co-morbidities (diabetes and hypertension). Similarly, place of residence (outside Patna district) (AOR = 2.38 [1.03-5.50]), co-morbidity (diabetes) (AOR = 3.08 [1.12-8.50]), intensive care unit (ICU) requirement at admission (yes) (AOR = 9.47 [3.98-22.52]) and COVID status (positive) (AOR = 6.33 [2.68-14.96]) were significant predictors of death among the study participants whereas place of residence (outside Patna district) (AOR = 4.04 [1.33-12.28]) and ICU requirement at admission (yes) (AOR = 7.22 [2.54-20.52]) were attributes affecting death of COVID-positive study participants. CONCLUSION: Risk of COVID-19 infection among the study participants was high. Age, gender and co-morbidities increased the risk of infection. COVID-19 infection negatively impacted the treatment outcome of the study participants. Age, co-morbidity and ICU requirement were the other attributes affecting mortality.

Intensive care management of patients with COVID-19.

The COVID-19 pandemic originated in China in December 2019 and has since then, swept across the world. The last Influenza pandemic of 1918 happened before the advent of modern medicine. We have come a long way since then. But the pandemic has still caught us unprepared in many quarters. The review focuses on the management of critically ill COVID-19 patients and the various challenges faced by intensivists.

Investigation of a Cluster of Severe Respiratory Disease Referred from Uganda to Kenya, February 2017.

On February 22, 2017, Hospital X-Kampala and US CDC-Kenya reported to the Uganda Ministry of Health a respiratory illness in a 46-year-old expatriate of Company A. The patient, Mr. A, was evacuated from Uganda to Kenya and died. He had recently been exposed to dromedary camels (MERS-CoV) and wild birds with influenza A (H5N6). We investigated the cause of illness, transmission, and recommended control. We defined a suspected case of severe acute respiratory illness (SARI) as acute onset of fever (≥38°C) with sore throat or cough and at least one of the following: headache, lethargy, or difficulty in breathing. In addition, we looked at cases with onset between February 1 and March 31 in a person with a history of contact with Mr. A, his family, or other Company A employees. A confirmed case was defined as a suspected case with laboratory confirmation of the same pathogen detected in Mr. A. Influenza-like illness was defined as onset of fever (≥38°C) and cough or sore throat in a Uganda contact, and as fever (≥38°C) and cough lasting less than 10 days in a Kenya contact. We collected Mr. A's exposure and clinical history, searched for cases, and traced contacts. Specimens from the index case were tested for complete blood count, liver function tests, plasma chemistry, Influenza A(H1N1)pdm09, and MERS-CoV. Robust field epidemiology, laboratory capacity, and cross-border communication enabled investigation.

COVID-19-Hospitalized Patients in Karnataka: Survival and Stay Characteristics.

The information on the clinical course of coronavirus disease 2019 (COVID-19) and its correlates which are essential to assess the hospital care needs of the population are currently limited. We investigated the factors associated with hospital stay and death for COVID-19 patients for the entire state of Karnataka, India. A retrospective-cohort analysis was conducted on 445 COVID-19 patients that were reported in the publicly available media-bulletin from March 9, 2020, to April 23, 2020, for the Karnataka state. This fixed cohort was followed till 14 days (May 8, 2020) for definitive outcomes (death/discharge). The median length of hospital stay was 17 days (interquartile range: 15-20) for COVID-19 patients. Having severe disease at the time of admission (adjusted-hazard-ratio: 9.3 (3.2-27.3);P < 0.001) and being aged ≥ 60 years (adjusted-hazard-ratio: 11.9 (3.5-40.6);P < 0.001) were the significant predictors of COVID-19 mortality. By moving beyond descriptive (which provide only crude information) to survival analyses, information on the local hospital-related characteristics will be crucial to model bed-occupancy demands for contingency planning during COVID-19 pandemic.