Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2

Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for epidemic control

Pathogen-pathogen interactions represent a critical but little-understood feature of infectious disease dynamics. In particular, experimental evidence suggests that influenza virus and respiratory syncytial virus (RSV) compete with each other, such that infection with one confers temporary protection against the other. However, such interactions are challenging to study using common epidemiologic methods. Here, we use a mathematical modeling approach, in conjunction with detailed surveillance data from Hong Kong and Canada, to infer the strength and duration of the interaction between influenza and RSV. Based on our estimates, we further utilize our model to evaluate the potential conflicting effects of live attenuated influenza vaccines (LAIV) on RSV burden. We find evidence of a moderate to strong, negative, bidirectional interaction, such that infection with either virus yields 40-100% protection against infection with the other for one to five months. Assuming that LAIV reduces RSV susceptibility in a similar manner, we predict that the impact of such a vaccine at the population level would likely depend greatly on underlying viral circulation patterns. More broadly, we highlight the utility of mathematical models as a tool to characterize pathogen-pathogen interactions.

Lethal synergistic infections by two concurrent respiratory pathogens

Lethal synergistic infections by concurrent pathogens have occurred in humans, including human immunodeficiency virus and Mycobacterium tuberculosis infections, or in animal or human models of influenza virus, or bacteria, e.g., Streptococcus pneumoniae, concurrent with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the intracellular synergistic interaction possibilities between two respiratory viral pathogens, or between viral and fungal pathogens, merits additional examination. The requirements for synergistic concurrent pathogen infections are: a) relatively little detrimental interference between two pathogens, b) one pathogen having the capability of directly or indirectly assisting the second pathogen by direct immuno-manipulation or indirect provision of infection opportunities and/or metabolic assistance, c) substantial human or environmental prevalence, possibly including a prevalence in any type of health-care facilities or other locations having congregations of potentially infected human or animal vectors and d) substantial transmissibility of the pathogens, which would make their concurrent pathogen infections much more probable. A new definition of pathogen synergy is proposed: "pathogen synergy is an interaction of two or more pathogens during concurrent infections causing an increased infection severity compared to mono-infections by the individual pathogens." Non-respiratory pathogens can also concurrently infect organs besides the lungs. However, the air-transmissible respiratory pathogens, particularly the RNA viruses, can enable highly widespread and synergistic concurrent infections. For instance, certain strains of coronaviruses, influenza viruses and similar respiratory viruses, are highly transmissible and/or widely prevalent in various vectors for transmission to humans and have numerous capabilities for altering lung immune defenses.

Early warning of emerging infectious diseases based on multimodal data

The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information. Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control. This review summarized the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants. As people have suffered from COVID-19 and repeated flu outbreaks, we focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses. This review comprehensively viewed the latest virus research and provided a reference for future virus prevention and control research.

The interactions of SARS-CoV-2 with cocirculating pathogens: Epidemiological implications and current knowledge gaps

Despite the availability of effective vaccines, the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggests that cocirculation with other pathogens and resulting multiepidemics (of, for example, COVID-19 and influenza) may become increasingly frequent. To better forecast and control the risk of such multiepidemics, it is essential to elucidate the potential interactions of SARS-CoV-2 with other pathogens; these interactions, however, remain poorly defined. Here, we aimed to review the current body of evidence about SARS-CoV-2 interactions. Our review is structured in four parts. To study pathogen interactions in a systematic and comprehensive way, we first developed a general framework to capture their major components: sign (either negative for antagonistic interactions or positive for synergistic interactions), strength (i.e., magnitude of the interaction), symmetry (describing whether the interaction depends on the order of infection of interacting pathogens), duration (describing whether the interaction is short-lived or long-lived), and mechanism (e.g., whether interaction modifies susceptibility to infection, transmissibility of infection, or severity of disease). Second, we reviewed the experimental evidence from animal models about SARS-CoV-2 interactions. Of the 14 studies identified, 11 focused on the outcomes of coinfection with nonattenuated influenza A viruses (IAVs), and 3 with other pathogens. The 11 studies on IAV used different designs and animal models (ferrets, hamsters, and mice) but generally demonstrated that coinfection increased disease severity compared with either monoinfection. By contrast, the effect of coinfection on the viral load of either virus was variable and inconsistent across studies. Third, we reviewed the epidemiological evidence about SARS-CoV-2 interactions in human populations. Although numerous studies were identified, only a few were specifically designed to infer interaction, and many were prone to multiple biases, including confounding. Nevertheless, their results suggested that influenza and pneumococcal conjugate vaccinations were associated with a reduced risk of SARS-CoV-2 infection. Finally, fourth, we formulated simple transmission models of SARS-CoV-2 cocirculation with an epidemic viral pathogen or an endemic bacterial pathogen, showing how they can naturally incorporate the proposed framework. More generally, we argue that such models, when designed with an integrative and multidisciplinary perspective, will be invaluable tools to resolve the substantial uncertainties that remain about SARS-CoV-2 interactions.

COVID-19 and Seasonal Influenza Vaccination: Cross-Protection, Co-Administration, Combination Vaccines, and Hesitancy

SARS-CoV-2 and influenza are the main respiratory viruses for which effective vaccines are currently available. Strategies in which COVID-19 and influenza vaccines are administered simultaneously or combined into a single preparation are advantageous and may increase vaccination uptake. Here, we comprehensively review the available evidence on COVID-19/influenza vaccine co-administration and combination vaccine candidates from the standpoints of safety, immunogenicity, efficacy, policy and public acceptance. While several observational studies have shown that the trained immunity induced by influenza vaccines can protect against some COVID-19-related endpoints, it is not yet understood whether co-administration or combination vaccines can exert additive effects on relevant outcomes. In randomized controlled trials, co-administration has proved safe, with a reactogenicity profile similar to that of either vaccine administered alone. From the immunogenicity standpoint, the immune response towards four influenza strains and the SARS-CoV-2 spike protein in co-administration groups is generally non-inferior to that seen in groups receiving either vaccine alone. Several public health authorities have advocated co-administration. Different combination vaccine candidates are in (pre)-clinical development. The hesitancy towards vaccine co-administration or combination vaccines is a multifaceted phenomenon and may be higher than the acceptance of either vaccine administered separately. Public health implications are discussed.