tetano
Editor, Senior Moderator
BMC Infect Dis
. 2022 Apr 4;22(1):331.
doi: 10.1186/s12879-022-07317-2.
The effectiveness of governmental nonpharmaceutical interventions against COVID-19 at controlling seasonal influenza transmission: an ecological study
Zekai Qiu[SUP] 1 2 [/SUP], Zicheng Cao[SUP] 1 2 [/SUP], Min Zou[SUP] 1 2 [/SUP], Kang Tang[SUP] 1 2 [/SUP], Chi Zhang[SUP] 1 2 [/SUP], Jing Tang[SUP] 1 2 [/SUP], Jinfeng Zeng[SUP] 1 2 [/SUP], Yaqi Wang[SUP] 1 2 [/SUP], Qianru Sun[SUP] 1 2 [/SUP], Daoze Wang[SUP] 1 2 [/SUP], Xiangjun Du[SUP] 3 4 5 [/SUP]
Affiliations
Abstract
Background: A range of strict nonpharmaceutical interventions (NPIs) were implemented in many countries to combat the coronavirus 2019 (COVID-19) pandemic. These NPIs may also be effective at controlling seasonal influenza virus infections, as influenza viruses have the same transmission path as severe acute respiratory syndrome coronavirus 2. The aim of this study was to evaluate the effects of different NPIs on the control of seasonal influenza.
Methods: Data for 14 NPIs implemented in 33 countries and the corresponding influenza virological surveillance data were collected. The influenza suppression index was calculated as the difference between the influenza positivity rate during its period of decline from 2019 to 2020 and during the influenza epidemic seasons in the previous 9 years. A machine learning model was developed using an extreme gradient boosting tree regressor to fit the NPI and influenza suppression index data. The SHapley Additive exPlanations tool was used to characterize the NPIs that suppressed the transmission of influenza.
Results: Of all NPIs tested, gathering limitations had the greatest contribution (37.60%) to suppressing influenza transmission during the 2019-2020 influenza season. The three most effective NPIs were gathering limitations, international travel restrictions, and school closures. For these three NPIs, their intensity threshold required to generate an effect were restrictions on the size of gatherings less than 1000 people, ban of travel to all regions or total border closures, and closing only some categories of schools, respectively. There was a strong positive interaction effect between mask-wearing requirements and gathering limitations, whereas merely implementing a mask-wearing requirement, and not other NPIs, diluted the effectiveness of mask-wearing requirements at suppressing influenza transmission.
Conclusions: Gathering limitations, ban of travel to all regions or total border closures, and closing some levels of schools were found to be the most effective NPIs at suppressing influenza transmission. It is recommended that the mask-wearing requirement be combined with gathering limitations and other NPIs. Our findings could facilitate the precise control of future influenza epidemics and other potential pandemics.
Keywords: Global; Influenza; Machine learning; Nonpharmaceutical interventions.
. 2022 Apr 4;22(1):331.
doi: 10.1186/s12879-022-07317-2.
The effectiveness of governmental nonpharmaceutical interventions against COVID-19 at controlling seasonal influenza transmission: an ecological study
Zekai Qiu[SUP] 1 2 [/SUP], Zicheng Cao[SUP] 1 2 [/SUP], Min Zou[SUP] 1 2 [/SUP], Kang Tang[SUP] 1 2 [/SUP], Chi Zhang[SUP] 1 2 [/SUP], Jing Tang[SUP] 1 2 [/SUP], Jinfeng Zeng[SUP] 1 2 [/SUP], Yaqi Wang[SUP] 1 2 [/SUP], Qianru Sun[SUP] 1 2 [/SUP], Daoze Wang[SUP] 1 2 [/SUP], Xiangjun Du[SUP] 3 4 5 [/SUP]
Affiliations
- PMID: 35379168
- DOI: 10.1186/s12879-022-07317-2
Abstract
Background: A range of strict nonpharmaceutical interventions (NPIs) were implemented in many countries to combat the coronavirus 2019 (COVID-19) pandemic. These NPIs may also be effective at controlling seasonal influenza virus infections, as influenza viruses have the same transmission path as severe acute respiratory syndrome coronavirus 2. The aim of this study was to evaluate the effects of different NPIs on the control of seasonal influenza.
Methods: Data for 14 NPIs implemented in 33 countries and the corresponding influenza virological surveillance data were collected. The influenza suppression index was calculated as the difference between the influenza positivity rate during its period of decline from 2019 to 2020 and during the influenza epidemic seasons in the previous 9 years. A machine learning model was developed using an extreme gradient boosting tree regressor to fit the NPI and influenza suppression index data. The SHapley Additive exPlanations tool was used to characterize the NPIs that suppressed the transmission of influenza.
Results: Of all NPIs tested, gathering limitations had the greatest contribution (37.60%) to suppressing influenza transmission during the 2019-2020 influenza season. The three most effective NPIs were gathering limitations, international travel restrictions, and school closures. For these three NPIs, their intensity threshold required to generate an effect were restrictions on the size of gatherings less than 1000 people, ban of travel to all regions or total border closures, and closing only some categories of schools, respectively. There was a strong positive interaction effect between mask-wearing requirements and gathering limitations, whereas merely implementing a mask-wearing requirement, and not other NPIs, diluted the effectiveness of mask-wearing requirements at suppressing influenza transmission.
Conclusions: Gathering limitations, ban of travel to all regions or total border closures, and closing some levels of schools were found to be the most effective NPIs at suppressing influenza transmission. It is recommended that the mask-wearing requirement be combined with gathering limitations and other NPIs. Our findings could facilitate the precise control of future influenza epidemics and other potential pandemics.
Keywords: Global; Influenza; Machine learning; Nonpharmaceutical interventions.