Dataset Information

An innovative influenza vaccination policy: targeting last season's patients.

ABSTRACT: Influenza vaccination is the primary approach to prevent influenza annually. WHO/CDC recommendations prioritize vaccinations mainly on the basis of age and co-morbidities, but have never considered influenza infection history of individuals for vaccination targeting. We evaluated such influenza vaccination policies through small-world contact networks simulations. Further, to verify our findings we analyzed, independently, large-scale empirical data of influenza diagnosis from the two largest Health Maintenance Organizations in Israel, together covering more than 74% of the Israeli population. These longitudinal individual-level data include about nine million cases of influenza diagnosed over a decade. Through contact network epidemiology simulations, we found that individuals previously infected with influenza have a disproportionate probability of being highly connected within networks and transmitting to others. Therefore, we showed that prioritizing those previously infected for vaccination would be more effective than a random vaccination policy in reducing infection. The effectiveness of such a policy is robust over a range of epidemiological assumptions, including cross-reactivity between influenza strains conferring partial protection as high as 55%. Empirically, our analysis of the medical records confirms that in every age group, case definition for influenza, clinical diagnosis, and year tested, patients infected in the year prior had a substantially higher risk of becoming infected in the subsequent year. Accordingly, considering individual infection history in targeting and promoting influenza vaccination is predicted to be a highly effective supplement to the current policy. Our approach can also be generalized for other infectious disease, computer viruses, or ecological networks.

SUBMITTER: Yamin D

PROVIDER: S-EPMC4031061 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An innovative influenza vaccination policy: targeting last season's patients.

Yamin Dan D Gavious Arieh A Solnik Eyal E Davidovitch Nadav N Balicer Ran D RD Galvani Alison P AP Pliskin Joseph S JS

PLoS computational biology 20140522 5

Influenza vaccination is the primary approach to prevent influenza annually. WHO/CDC recommendations prioritize vaccinations mainly on the basis of age and co-morbidities, but have never considered influenza infection history of individuals for vaccination targeting. We evaluated such influenza vaccination policies through small-world contact networks simulations. Further, to verify our findings we analyzed, independently, large-scale empirical data of influenza diagnosis from the two largest He ...[more]

PMID: 24851863

Similar Datasets

Project description:BackgroundImmunocompromised patients are vulnerable to severe or complicated influenza infection. Vaccination is widely recommended for this group. This systematic review and meta-analysis assesses influenza vaccination for immunocompromised patients in terms of preventing influenza-like illness and laboratory confirmed influenza, serological response and adverse events.Methodology/principal findingsElectronic databases and grey literature were searched and records were screened against eligibility criteria. Data extraction and risk of bias assessments were performed in duplicate. Results were synthesised narratively and meta-analyses were conducted where feasible. Heterogeneity was assessed using I(2) and publication bias was assessed using Begg's funnel plot and Egger's regression test. Many of the 209 eligible studies included an unclear or high risk of bias. Meta-analyses showed a significant effect of preventing influenza-like illness (odds ratio [OR]=0.23; 95% confidence interval [CI]=0.16-0.34; p<0.001) and laboratory confirmed influenza infection (OR=0.15; 95% CI=0.03-0.63; p=0.01) through vaccinating immunocompromised patie nts compared to placebo or unvaccinated controls. We found no difference in the odds of influenza-like illness compared to vaccinated immunocompetent controls. The pooled odds of seroconversion were lower in vaccinated patients compared to immunocompetent controls for seasonal influenza A(H1N1), A(H3N2) and B. A similar trend was identified for seroprotection. Meta-analyses of seroconversion showed higher odds in vaccinated patients compared to placebo or unvaccinated controls, although this reached significance for influenza B only. Publication bias was not detected and narrative synthesis supported our findings. No consistent evidence of safety concerns was identified.Conclusions/significanceInfection prevention and control strategies should recommend vaccinating immunocompromised patients. Potential for bias and confounding and the presence of heterogeneity mean the evidence reviewed is generally weak, although the directions of effects are consistent. Areas for further research are identified.

Project description:Understanding positive and negative influences on adult immunization status can help healthcare providers to better identify and target patients who are likely to need immunization. Our aim was to assess and compare influenza and pneumococcal (IV/PV) immunisation rates to identify vaccination predictors in Malta.One group consisted of all medical patients discharged from Mater Dei Hospital (MDH) over a one week period in February 2013. Patients were administered a phone questionnaire. A second group of patients receiving community-based care at local health centres over a one week period in March 2013 were interviewed, identifying vaccination eligibility as per 2010 WHO recommendations.A total of 150 community (Mean age 61.5 SD 15.8, Male 60%) and 149 hospitalised (Mean age 66.8, SD 13.6%, Male 48.3%) patients in whom influenza vaccine was indicated were recruited. In the current year, 44 and 48.3% received the seasonal influenza vaccine, while 32.0, and 49% vaccinated yearly respectively. Pneumococcal vaccination advice was less than 5% in both groups. On stepwise binary regression, vaccination predictors for the current year were regular yearly influenza vaccination (OR 93.62, CI: 31.8-275.5, p <?0.001) and vaccination reminders (OR 27.5, CI: 9.63-78.31, p?<?0.001). Nursing home residence (OR 5.78, CI: 1.22-27.4,p =?0.011), congestive cardiac failure (OR 2.11, CI: 1.1-4.08, p =?0.02) and diabetes mellitus (OR 1.68, CI: 1.04-2.72, p =?0.034) were all predictors for vaccination on exclusion of the strongest two predictors. For successive yearly vaccination, influenza vaccine recommendation by healthcare professionals (OR 12.35, CI: 4.5-33.91, p <?0.001) and vaccination reminders (OR 5.99, CI: 3.13-11.45, p <?0.01) were main predictors. Congestive cardiac failure (OR 2.37, CI: 1.20-4.7, p =?0.13) and nursing home residence (OR 7.07, CI: 1.45-34.5, p?=?0,005) were also positive predictors. Male gender was a negative predictor (OR 0.51, CI: 0.31-0.83, p =?0.006). Some of those who did not vaccinate were unaware of such need (40.5% of community and 15.6% of hospitalised patients).Just under half of the patient population received the IV during 2012-2013 period. Hospitalized patients are more likely to vaccinate regularly while a large proportion of community patients are unaware of the indication to vaccinate.

Dataset Information

An innovative influenza vaccination policy: targeting last season's patients.

Publications

An innovative influenza vaccination policy: targeting last season's patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets