Shifting the Demand for Vaccines: A Review of Strategies.

Vaccines prevent millions of deaths, and yet millions of people die each year from vaccine-preventable diseases. The primary reason for these deaths is that a significant fraction of the population chooses not to vaccinate. Why don't people vaccinate, and what can be done to increase vaccination rates besides providing free and easy access to vaccines? This review presents a conceptual framework, motivated by economic theory, of which factors shift the demand for vaccines. Next, it critically examines the literature on these demand shifters and interventions that target these demand shifters. The review concludes with offering directions for future research and lessons for public health decision making.

Systematic identification and replication of factors associated with human papillomavirus vaccine initiation among adolescents in the United States using an environment-wide association study approach.

OBJECTIVE: Human papillomavirus (HPV) vaccination coverage is low among adolescents in the USA. Identification of factors associated with HPV vaccine initiation (receipt of ≥1 dose) is critical for improving uptake. Our objective was to systematically investigate all eligible factors available in a nationally representative sample of adolescents to identify drivers of HPV vaccine initiation using a novel methodological approach. METHODS: We performed multiple cross-sectional analyses using data from the adolescent component of the National Immunization Surveys (NIS)-Teen between 2014 and 2019. Study participants were parents or caregivers of adolescents aged 13-17 years. Exposure variables measured sociodemographic and geographical characteristics, health conditions and healthcare provision. We tested the association between each factor and HPV vaccine initiation using univariate logistic regression and multivariate logistic regression adjusted for mother's age, mother's education level, mother's marital status, poverty status and adolescent's sex. We validated findings for each type of analysis within surveys, between surveys (across years 2014-2019) and across several subgroups (age, sex, poverty status and race/ethnicity). RESULTS: Six factors were replicated in the multivariate analysis. Most replicated factors characterised the role of healthcare providers and healthcare-seeking behaviours. After adjustment, provider HPV recommendation remained the most strongly associated with HPV vaccine initiation (2019 NIS-Teen: OR 13.4, 95% CI 11.3 to 17.3, p<0.001). The variance explained by a full model including replicated factors was 0.39. CONCLUSIONS: This is the first study to explore the association between all available factors in the NIS-Teen and HPV vaccine initiation in a systematic manner. Our study suggests that healthcare-seeking behaviours and interactions with the health system may be drivers of HPV vaccine initiation and warrant further study. Addressing these factors could improve the rate of HPV vaccine initiation among adolescents in the USA.

Assessment of the Frequency and Variety of Persistent Symptoms Among Patients With COVID-19: A Systematic Review.

Importance: Infection with COVID-19 has been associated with long-term symptoms, but the frequency, variety, and severity of these complications are not well understood. Many published commentaries have proposed plans for pandemic control that are primarily based on mortality rates among older individuals without considering long-term morbidity among individuals of all ages. Reliable estimates of such morbidity are important for patient care, prognosis, and development of public health policy. Objective: To conduct a systematic review of studies examining the frequency and variety of persistent symptoms after COVID-19 infection. Evidence Review: A search of PubMed and Web of Science was conducted to identify studies published from January 1, 2020, to March 11, 2021, that examined persistent symptoms after COVID-19 infection. Persistent symptoms were defined as those persisting for at least 60 days after diagnosis, symptom onset, or hospitalization or at least 30 days after recovery from the acute illness or hospital discharge. Search terms included COVID-19, SARS-CoV-2, coronavirus, 2019-nCoV, long-term, after recovery, long-haul, persistent, outcome, symptom, follow-up, and longitudinal. All English-language articles that presented primary data from cohort studies that reported the prevalence of persistent symptoms among individuals with SARS-CoV-2 infection and that had clearly defined and sufficient follow-up were included. Case reports, case series, and studies that described symptoms only at the time of infection and/or hospitalization were excluded. A structured framework was applied to appraise study quality. Findings: A total of 1974 records were identified; of those, 1247 article titles and abstracts were screened. After removal of duplicates and exclusions, 92 full-text articles were assessed for eligibility; 47 studies were deemed eligible, and 45 studies reporting 84 clinical signs or symptoms were included in the systematic review. Of 9751 total participants, 5266 (54.0%) were male; 30 of 45 studies reported mean or median ages younger than 60 years. Among 16 studies, most of which comprised participants who were previously hospitalized, the median proportion of individuals experiencing at least 1 persistent symptom was 72.5% (interquartile range [IQR], 55.0%-80.0%). Individual symptoms occurring most frequently included shortness of breath or dyspnea (26 studies; median frequency, 36.0%; IQR, 27.6%-50.0%), fatigue or exhaustion (25 studies; median frequency, 40.0%; IQR, 31.0%-57.0%), and sleep disorders or insomnia (8 studies; median 29.4%, IQR, 24.4%-33.0%). There were wide variations in the design and quality of the studies, which had implications for interpretation and often limited direct comparability and combinability. Major design differences included patient populations, definitions of time zero (ie, the beginning of the follow-up interval), follow-up lengths, and outcome definitions, including definitions of illness severity. Conclusions and Relevance: This systematic review found that COVID-19 symptoms commonly persisted beyond the acute phase of infection, with implications for health-associated functioning and quality of life. Current studies of symptom persistence are highly heterogeneous, and future studies need longer follow-up, improved quality, and more standardized designs to reliably quantify risks.

Association between air travel and importation of chikungunya into the USA.

Background: During infectious disease outbreaks with pandemic potential, the number of air passengers travelling from the outbreak source to international destinations has been used as a proxy for disease importation risk to new locations. However, evaluations of the validity of this approach are limited. We sought to quantify the association between international air travel and disease importation using the 2014-2016 chikungunya outbreak in the Americas as a case study.Methods: We used country-level chikungunya case data to define a time period of epidemic activity for each of the 45 countries and territories in the Americas reporting outbreaks between 2014 and 2016. For each country, we identified airports within or proximate to areas considered suitable for chikungunya transmission and summed the number of commercial air passengers departing from these airports during the epidemic period to each US state. We used negative binomial models to quantify the association between the number of incoming air passengers from countries experiencing chikungunya epidemics and the annual rate of chikungunya importation into the USA at the state level.Results: We found a statistically significant positive association between passenger flows via airline travel from countries experiencing chikungunya epidemics and the number of imported cases in the USA at the state level (P < 0.0001). Additionally, we found that as the number of arriving airline passengers increased by 10%, the estimated number of imported cases increased by 5.2% (95% CI: 3.0-7.6).Conclusion: This validation study demonstrated that air travel was strongly associated with observed importation of chikungunya cases in the USA and can be a useful proxy for identifying areas at increased risk for disease importation. This approach may be useful for understanding exportation risk of other arboviruses.

Relatedness of the incidence decay with exponential adjustment (IDEA) model, "Farr's law" and SIR compartmental difference equation models.

Mathematical models are often regarded as recent innovations in the description and analysis of infectious disease outbreaks and epidemics, but simple mathematical expressions have been in use for projection of epidemic trajectories for more than a century. We recently introduced a single equation model (the incidence decay with exponential adjustment, or IDEA model) that can be used for short-term epidemiological forecasting. In the mid-19th century, Dr. William Farr made the observation that epidemic events rise and fall in a roughly symmetrical pattern that can be approximated by a bell-shaped curve. He noticed that this time-evolution behavior could be captured by a single mathematical formula ("Farr's law") that could be used for epidemic forecasting. We show here that the IDEA model follows Farr's law, and show that for intuitive assumptions, Farr's Law can be derived from the IDEA model. Moreover, we show that both mathematical approaches, Farr's Law and the IDEA model, resemble solutions of a susceptible-infectious-removed (SIR) compartmental differential-equation model in an asymptotic limit, where the changes of disease transmission respond to control measures, and not only to the depletion of susceptible individuals. This suggests that the concept of the reproduction number ( R 0 ) was implicitly captured in Farr's (pre-microbial era) work, and also suggests that control of epidemics, whether via behavior change or intervention, is as integral to the natural history of epidemics as is the dynamics of disease transmission.

Seasonal Influenza Forecasting in Real Time Using the Incidence Decay With Exponential Adjustment Model.

BACKGROUND: Seasonal influenza epidemics occur frequently. Rapid characterization of seasonal dynamics and forecasting of epidemic peaks and final sizes could help support real-time decision-making related to vaccination and other control measures. Real-time forecasting remains challenging. METHODS: We used the previously described "incidence decay with exponential adjustment" (IDEA) model, a 2-parameter phenomenological model, to evaluate the characteristics of the 2015-2016 influenza season in 4 Canadian jurisdictions: the Provinces of Alberta, Nova Scotia and Ontario, and the City of Ottawa. Model fits were updated weekly with receipt of incident virologically confirmed case counts. Best-fit models were used to project seasonal influenza peaks and epidemic final sizes. RESULTS: The 2015-2016 influenza season was mild and late-peaking. Parameter estimates generated through fitting were consistent in the 2 largest jurisdictions (Ontario and Alberta) and with pooled data including Nova Scotia counts (R0 approximately 1.4 for all fits). Lower R0 estimates were generated in Nova Scotia and Ottawa. Final size projections that made use of complete time series were accurate to within 6% of true final sizes, but final size was using pre-peak data. Projections of epidemic peaks stabilized before the true epidemic peak, but these were persistently early (~2 weeks) relative to the true peak. CONCLUSIONS: A simple, 2-parameter influenza model provided reasonably accurate real-time projections of influenza seasonal dynamics in an atypically late, mild influenza season. Challenges are similar to those seen with more complex forecasting methodologies. Future work includes identification of seasonal characteristics associated with variability in model performance.