Back

Epidemiology and burden of respiratory syncytial virus in Italian adults: A systematic review and meta-analysis

Domnich, A.; Calabro'|, G. E.

2024-01-13 epidemiology
10.1101/2024.01.11.24301142 medRxiv
Show abstract

ObjectiveRespiratory syncytial virus (RSV) is a common respiratory pathogen not only in children, but also in adults. Country-specific data on the epidemiology and burden of disease are essential for policy decisions. In view of a recent authorization of adult RSV vaccines, we aimed to comprehensively collect and assess evidence on the epidemiology and burden of RSV in Italian adults. MethodsA systematic literature review was conducted according to the available guidelines. Random-effects proportional meta-analysis was performed to obtain pooled estimates and the observed heterogeneity was investigated by using both subgroup and meta-regression analyses. ResultsA total of 35 studies were identified. RSV seasonal attack rates ranged from 0.8 {per thousand} in community-dwelling older adults to 10.9% in hematological outpatients. On average, 4.5% (95% CI: 3.2-5.9%) of respiratory samples tested positive for RSV. This positivity prevalence was higher in older adults (4.4%; 95% CI: 2.8- 6.3%) than in working-age adults (3.5%; 95% CI: 2.5-4.6%) and in outpatient (4.9%; 95% CI: 3.1-7.0%) than inpatient (2.9%; 95% CI: 1.5-4.8%) settings. Study location and sample size were also significant predictors of RSV detection frequency. The pooled estimate of in-hospital mortality was as high as 7.2% (95% CI: 4.7- 10.3%). However, other important indicators of the diseases burden, such as complication and hospitalization rates, are missing. ConclusionRSV poses a measurable burden on Italian adults, especially those of older age and with some co-morbidities. Policy makers should give priority to health technology assessment of the novel RSV vaccines.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.