The effect of COVID-19 stay-at-home order and campus closure on the prevalence of acute respiratory infection symptoms in college campus cohorts.

Evaluation of population-based COVID-19 control measures informs strategies to quell the current pandemic and reduce the impact of those yet to come. Effective COVID-19 control measures may simultaneously reduce the incidence of other acute respiratory infections (ARIs) due to shared transmission modalities. To assess the impact of stay-at-home orders and other physical distancing measures on the prevalence of ARI-related symptoms, we compared symptoms reported by prospective college cohorts enrolled during two consecutive academic years. ARI-related symptoms declined following campus closure and implementation of stay-at-home orders, demonstrating the impact of population-based physical distancing measures on control of a broad range of respiratory infections.

Influenza A (H3) illness and viral aerosol shedding from symptomatic naturally infected and experimentally infected cases.

BACKGROUND: It has long been known that nasal inoculation with influenza A virus produces asymptomatic to febrile infections. Uncertainty persists about whether these infections are sufficiently similar to natural infections for studying human-to-human transmission. METHODS: We compared influenza A viral aerosol shedding from volunteers nasally inoculated with A/Wisconsin/2005 (H3N2) and college community adults naturally infected with influenza A/H3N2 (2012-2013), selected for influenza-like illness with objectively measured fever or a positive Quidel QuickVue A&B test. Propensity scores were used to control for differences in symptom presentation observed between experimentally and naturally infected groups. RESULTS: Eleven (28%) experimental and 71 (86%) natural cases shed into fine particle aerosols (P < .001). The geometric mean (geometric standard deviation) for viral positive fine aerosol samples from experimental and natural cases was 5.1E + 3 (4.72) and 3.9E + 4 (15.12) RNA copies/half hour, respectively. The 95th percentile shedding rate was 2.4 log10 greater for naturally infected cases (1.4E + 07 vs 7.4E + 04). Certain influenza-like illness-related symptoms were associated with viral aerosol shedding. The almost complete lack of symptom severity distributional overlap between groups did not support propensity score-adjusted shedding comparisons. CONCLUSIONS: Due to selection bias, the natural and experimental infections had limited symptom severity distributional overlap precluding valid, propensity score-adjusted comparison. Relative to the symptomatic naturally infected cases, where high aerosol shedders were found, experimental cases did not produce high aerosol shedders. Studying the frequency of aerosol shedding at the highest observed levels in natural infections without selection on symptoms or fever would support helpful comparisons.

Quantitative aerobiologic analysis of an influenza human challenge-transmission trial.

Despite evidence that airborne transmission contributes to influenza epidemics, limited knowledge of the infectiousness of human influenza cases hinders pandemic preparedness. We used airborne viral source strength and indoor CO2 monitoring from the largest human influenza challenge-transmission trial (EMIT: Evaluating Modes of Influenza Transmission, ClinicalTrials.gov number NCT01710111) to compute an airborne infectious dose generation rate q = 0.11 (95% CI 0.088, 0.12)/h and calculate the quantity of airborne virus per infectious dose σ = 1.4E + 5 RNA copies/quantum (95% CI 9.9E + 4, 1.8E + 5). We then compared these calculated values to available data on influenza airborne infectious dose from several previous studies, and applied the values to dormitory room environments to predict probability of transmission between roommates. Transmission risk from typical, moderately to severely symptomatic influenza cases is dramatically decreased by exposure reduction via increasing indoor air ventilation. The minority of cases who shed the most virus (ie, supershedders) may pose great risk even in well-ventilated spaces. Our modeling method and estimated infectiousness provide a ground work for (a) epidemiologic studies of transmission in non-experimental settings and (b) evaluation of the extent to which airborne exposure control strategies could limit transmission risk.