Epidemiology of Pediatric Respiratory Tract Infections During the COVID-19 Era: A Retrospective Multicentric Study of Hospitalized Children in Lebanon Between October 2018 and March 2021.

Background The identification of SARS-CoV-2 in December 2019 and its subsequent designation as the causative agent of COVID-19 marked the beginning of an unprecedented global health crisis. As the virus spread rapidly across continents, its impact on various demographic groups, including children, became a subject of intense research. While children were initially thought to be less susceptible to severe COVID-19 illness compared to adults, concerns emerged regarding their vulnerability to other respiratory infections amidst the pandemic. Understanding the epidemiological trends of pediatric respiratory tract infections (RTIs) during the COVID-19 era is crucial for informing public health strategies and clinical management protocols. This study aimed to compare the prevalence and characteristics of pediatric RTIs before and during the COVID-19 pandemic in Lebanon. Methodology A retrospective, observational study was conducted by reviewing medical records of children admitted to three tertiary care hospitals in Lebanon: Sheikh Ragheb Harb University Hospital, Al Sahel General University Hospital, and Rafik Al-Hariri University Hospital. Data were collected from October 2018 to March 2021, encompassing both the pre-COVID-19 and COVID-19 eras. A standardized data collection sheet was utilized to gather information on demographic characteristics, clinical presentations, duration of hospitalization, and antibiotic usage. Results Our analysis revealed significant shifts in the epidemiology of pediatric RTIs between the pre-COVID-19 and COVID-19 eras. There was a marked decline in the proportion of school-age children hospitalized with RTIs during the pandemic period. However, the overall percentage of Lebanese hospitalized children across different age groups increased significantly during the COVID-19 era. Furthermore, the prevalence of specific RTIs, such as pharyngitis, increased from 1.1% in the pre-COVID-19 to 5.5% during the COVID-19 period (p = 0.016), and the prevalence of bronchiolitis increased from 26.7% to 50.9% (p < 0.001) during the pre-COVID-19 and COVID-19 periods, respectively. This notable rise during the pandemic suggested potential changes in circulating pathogens or diagnostic practices. Importantly, the median length of hospital stays for pediatric RTIs decreased during the COVID-19 era compared to the pre-pandemic period, indicating possible improvements in clinical management or healthcare resource utilization. Analysis of antibiotic usage revealed ceftriaxone as the most frequently prescribed antibiotic in both periods, highlighting its continued relevance in the management of pediatric RTIs. Conclusions This study highlights significant epidemiological shifts in pediatric RTIs during the COVID-19 era in Lebanon. These findings underscore the importance of ongoing surveillance and research to adapt public health interventions and clinical practices to evolving infectious disease dynamics. Further investigation is warranted to elucidate the underlying factors driving these changes and optimize strategies for the prevention and management of pediatric RTIs in the context of the ongoing pandemic.

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources, with application to COVID-19.

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.

A robust pooled testing approach to expand COVID-19 screening capacity.

Limited testing capacity for COVID-19 has hampered the pandemic response. Pooling is a testing method wherein samples from specimens (e.g., swabs) from multiple subjects are combined into a pool and screened with a single test. If the pool tests positive, then new samples from the collected specimens are individually tested, while if the pool tests negative, the subjects are classified as negative for the disease. Pooling can substantially expand COVID-19 testing capacity and throughput, without requiring additional resources. We develop a mathematical model to determine the best pool size for different risk groups, based on each group's estimated COVID-19 prevalence. Our approach takes into consideration the sensitivity and specificity of the test, and a dynamic and uncertain prevalence, and provides a robust pool size for each group. For practical relevance, we also develop a companion COVID-19 pooling design tool (through a spread sheet). To demonstrate the potential value of pooling, we study COVID-19 screening using testing data from Iceland for the period, February-28-2020 to June-14-2020, for subjects stratified into high- and low-risk groups. We implement the robust pooling strategy within a sequential framework, which updates pool sizes each week, for each risk group, based on prior week's testing data. Robust pooling reduces the number of tests, over individual testing, by 88.5% to 90.2%, and 54.2% to 61.9%, respectively, for the low-risk and high-risk groups (based on test sensitivity values in the range [0.71, 0.98] as reported in the literature). This results in much shorter times, on average, to get the test results compared to individual testing (due to the higher testing throughput), and also allows for expanded screening to cover more individuals. Thus, robust pooling can potentially be a valuable strategy for COVID-19 screening.