Mitigating co-circulation of seasonal influenza and COVID-19 pandemic in the presence of vaccination: A mathematical modeling approach

Abstract

The co-circulation of two respiratory infections with similar symptoms in a population can significantly overburden a healthcare system by slowing the testing and treatment. The persistent emergence of contagious variants of SARS-CoV-2, along with imperfect vaccines and their waning protections, have increased the likelihood of new COVID-19 outbreaks taking place during a typical flu season. Here, we developed a mathematical model for the co-circulation dynamics of COVID-19 and influenza, under different scenarios of influenza vaccine coverage, COVID-19 vaccine booster coverage and efficacy, and testing capacity. We investigated the required minimal and optimal coverage of COVID-19 booster (third) and fourth doses, in conjunction with the influenza vaccine, to avoid the coincidence of infection peaks for both diseases in a single season. We show that the testing delay brought on by the high number of influenza cases impacts the dynamics of influenza and COVID-19 transmission. The earlier the peak of the flu season and the greater the number of infections with flu-like symptoms, the greater the risk of flu transmission, which slows down COVID-19 testing, resulting in the delay of complete isolation of patients with COVID-19 who have not been isolated before the clinical presentation of symptoms and have been continuing their normal daily activities. Furthermore, our simulations stress the importance of vaccine uptake for preventing infection, severe illness, and hospitalization at the individual level and for disease outbreak control at the population level to avoid putting strain on already weak and overwhelmed healthcare systems. As such, ensuring optimal vaccine coverage for COVID-19 and influenza to reduce the burden of these infections is paramount. We showed that by keeping the influenza vaccine coverage about 35% and increasing the coverage of booster or fourth dose of COVID-19 not only reduces the infections with COVID-19 but also can delay its peak time. If the influenza vaccine coverage is increased to 55%, unexpectedly, it increases the peak size of influenza infections slightly, while it reduces the peak size of COVID-19 as well as significantly delays the peaks of both of these diseases. Mask-wearing coupled with a moderate increase in the vaccine uptake may mitigate COVID-19 and prevent an influenza outbreak.

Volatility of the COVID-19 vaccine hesitancy: sentiment analysis conducted in Brazil

“…Such availability caused those who were hesitant to manifest their opinion with greater intensity. Despite the existence of COVID-19 variants circulating in Brazil, we did not encounter any manifestation of VH related to this issue (48).…”

“…These initial manifestations express concerns with the source of the vaccine, i.e., with which laboratory is developing it, highlighting the need for the government to establish partnerships with research and production laboratories to provide as much information as possible. Subsequent evidence showed that some vaccines were imperfect or even had a declining protection index, thus favoring new COVID-19 outbreaks (48). In Brazil some politicians assured that the vaccine made contamination impossible, which increased VH when the first cases of contamination by COVID-19 of vaccinated people surfaced.…”

“…The benefit of the cooling of the COVID-19 pandemic should not impact the importance of VH research, as there are other infections that spread in waves, affecting all of society. One example is the influenza virus responsible for infecting 1 billion people per year (48,71), resulting in 290,000 to 650,000 influenza-related respiratory deaths (72).…”

Mechanism design for a fair and equitable approach to global vaccine distribution: The case of COVID-19

“…In the past, they have helped in the elimination of polio and the eradication of smallpox [ 26 ]. They hold the potential to protect humanity against morbidity and mortality from current and future epidemics [ 27 ]. Nonetheless, the distribution and allocation of vaccines to where they are needed the most in the world is a challenge.…”

An Epidemic Model with Infection Age and Vaccination Age Structure

“…The literature on epidemic models is extensive, with structure variables and vaccination elements. In our References, we have listed many of such works [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 …”