Global patterns in monthly activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus: a systematic analysis

Abstract

Background Influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus are the most common viruses associated with acute lower respiratory infections in young children (<5 years) and older people (≥65 years). A global report of the monthly activity of these viruses is needed to inform public health strategies and programmes for their control. Methods In this systematic analysis, we compiled data from a systematic literature review of studies published between Jan 1, 2000, and Dec 31, 2017; online datasets; and unpublished research data. Studies were eligible for inclusion if they reported laboratory-confirmed incidence data of human infection of influenza virus, respiratory syncytial virus, parainfluenza virus, or metapneumovirus, or a combination of these, for at least 12 consecutive months (or 52 weeks equivalent); stable testing practice throughout all years reported; virus results among residents in well-defined geographical locations; and aggregated virus results at least on a monthly basis. Data were extracted through a threestage process, from which we calculated monthly annual average percentage (AAP) as the relative strength of virus activity. We defined duration of epidemics as the minimum number of months to account for 75% of annual positive samples, with each component month defined as an epidemic month. Furthermore, we modelled monthly AAP of influenza virus and respiratory syncytial virus using site-specific temperature and relative humidity for the prediction of local average epidemic months. We also predicted global epidemic months of influenza virus and respiratory syncytial virus on a 5° by 5° grid. The systematic review in this study is registered with PROSPERO, number CRD42018091628. Findings We initally identified 37 335 eligible studies. Of 21 065 studies remaining after exclusion of duplicates, 1081 full-text articles were assessed for eligibility, of which 185 were identified as eligible. We included 246 sites for influenza virus, 183 sites for respiratory syncytial virus, 83 sites for parainfluenza virus, and 65 sites for metapneumovirus. Influenza virus had clear seasonal epidemics in winter months in most temperate sites but timing of epidemics was more variable and less seasonal with decreasing distance from the equator. Unlike influenza virus, respiratory syncytial virus had clear seasonal epidemics in both temperate and tropical regions, starting in late summer months in the tropics of each hemisphere, reaching most temperate sites in winter months. In most temperate sites, influenza virus epidemics occurred later than respiratory syncytial virus (by 0•3 months [95% CI-0•3 to 0•9]) while no clear temporal order was observed in the tropics. Parainfluenza virus epidemics were found mostly in spring and early summer months in each hemisphere. Metapneumovirus epidemics occurred in late winter and spring in most temperate sites but the timing of epidemics was more diverse in the tropics. Influenza virus epidemics had shorter duration (3•8 months [3•6 to 4•0]) i...

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“…A systematic analysis on global patterns in monthly activity of influenza virus, respiratory syncytial virus, parainfluenza virus, and metapneumovirus found influenza virus had clear seasonal epidemics in winter months in most temperate sites but timing of epidemics was more variable and less seasonal with decreasing distance from the equator and other viruses had obvious epidemic seasons. [14] In our data, S. aureus had the highest isolation rate in spring, A. baumannii, H. influenzae and S. pneumoniae had the highest isolation rate in summer, K. pneumoniae, P. aeruginosa and S. maltophilia had the highest isolation rate in autumn, while E. coli had the highest isolation rate in winter. It is of great significance to understand the seasonal prevalence of pathogens in LRIs for disease prevention and control as well as vaccination.…”

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“…14 settings. 32,33 This knowledge will be crucial to inform potential public health interventions to reduce disease burden in the population.…”

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