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.

Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018-2020.

Despite its critical role in containing outbreaks, the efficacy of contact tracing, measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of contact tracing by applying unilist capture-recapture methods on data from the 2018-2020 outbreak of Ebola virus disease in the Democratic Republic of the Congo. To compute sensitivity, we applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved case-patients with any contacts and infected contacts. Geometric distributions were the best-fitting models. Our results indicate that contact tracing efforts identified almost all (n = 792, 99%) of case-patients with any contacts but only half (n = 207, 48%) of case-patients with infected contacts, suggesting that contact tracing efforts performed well at identifying contacts during the listing stage but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the ongoing coronavirus pandemic.

Healthcare-associated outbreaks of bacterial infections in Africa, 2009-2018: A review.

BACKGROUND: Healthcare-associated infections (HAIs) are a major global public health problem, increasing the transmission of drug-resistant infections. In Africa, the prevalence of HAIs among all hospital inpatients is estimated to be between 3% and 15%, but outbreaks are infrequently reported. Failure to detect and/or report outbreaks can increase the risk of ongoing infections and recurrent outbreaks. METHODS: A search of the PubMed, Web of Science, Cochrane Library, and other outbreak databases was performed to identify published literature on bacterial HAI outbreaks in Africa (January 2009 to December 2018). Details of the outbreak characteristics, hospital environment, and the control measures implemented were extracted. RESULTS: Twenty-two studies published over the 10-year period were identified. These reported 31 distinct outbreaks and a total of 31 causative pathogens, including Klebsiella pneumoniae (six outbreaks, 19%), Staphylococcus aureus (six outbreaks, 19%), and Enterococcus (five outbreaks, 16%). Most outbreaks were reported from university (n = 8, 26%) and tertiary hospitals (n = 11, 55%), from South Africa (n = 9, 41%) and Tunisia (n = 4, 18%). Interventions to control the outbreaks were described in 27 (90%) outbreaks, and all instituted or recommended enhancing hand hygiene and education. CONCLUSIONS: Few facilities in Africa reported HAI outbreaks over the 10-year period, suggesting substantial under-detection and under-reporting. The quality and timeliness of reporting require improvement to ensure changes in public health practice.

Unbiased assessment of disease surveillance utilities: A prospect theory application.

OBJECTIVES: We contribute a new methodological approach to the ongoing efforts towards evaluating public health surveillance. Specifically, we apply a descriptive framework, grounded in prospect theory (PT), for the evaluation of decisions on disease surveillance deployment. We focus on two attributes of any surveillance system: timeliness, and false positive rate (FPR). METHODS: In a sample of 69 health professionals from a number of health related networks polled online, we elicited PT preferences, specifically respondents' attitudes towards gains, losses and probabilities (i.e., if they overweight or underweight extreme probabilities) by means of a series of lotteries for either timeliness or FPR. Moreover, we estimated willingness to pay (WTP) for improvements in the two surveillance attributes. For contextualization, we apply our framework to rabies surveillance. RESULTS: Our data reveal considerable probability weighting, both for gains and losses. In other words, respondents underestimate their chances of getting a good outcome in uncertain situations, and they overestimate their chances of bad outcomes. Moreover, there is convex utility for losses and loss aversion, that is, losses loom larger than gains of the same absolute magnitude to the respondents. We find no differences between the estimated parameters for timeliness and FPR. The median WTP is $7,250 per day gained in detection time and $30 per 1/10,000 reduction in FPR. CONCLUSION: Our results indicate that the biases described by PT are present among public health professionals, which highlights the need to incorporate a PT framework when eliciting their preferences for surveillance systems.

Cystic echinococcosis in South America: a call for action.

Cystic echinococcosis (CE) or hydatidosis, a parasitic zoonosis caused by a cestode of the family Taeniidae, species Echinococcus granulosus, is endemic in Argentina, Chile, Peru, Uruguay, and southern Brazil. This report presents CE figures for these five countries in 2009 - 2014 and proposes indicators to measure national control programs. Nearly 5 000 new CE cases were diagnosed annually in the five countries during the study period. The average case fatality rate was 2.9%, which suggests that CE led to approximately 880 deaths in these countries during the 6-year period. CE cases that required secondary or tertiary health care had average hospital stays of 10.6 days, causing a significant burden to health systems. The proportion of new cases (15%) in children less than 15 years of age suggests ongoing transmission. Despite figures showing that CE is not under control in South America, the long-standing implementation of national and local control programs in three of the five countries has achieved reductions in some of the indicators. The Regional Initiative for the Control of CE, which includes the five countries and provides a framework for networking and collaboration, must intensify its efforts.

A Practitioner-Driven Research Agenda for Syndromic Surveillance.

Syndromic surveillance has expanded since 2001 in both scope and geographic reach and has benefited from research studies adapted from numerous disciplines. The practice of syndromic surveillance continues to evolve rapidly. The International Society for Disease Surveillance solicited input from its global surveillance network on key research questions, with the goal of improving syndromic surveillance practice. A workgroup of syndromic surveillance subject matter experts was convened from February to June 2016 to review and categorize the proposed topics. The workgroup identified 12 topic areas in 4 syndromic surveillance categories: informatics, analytics, systems research, and communications. This article details the context of each topic and its implications for public health. This research agenda can help catalyze the research that public health practitioners identified as most important.