Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023
Abstract Objectives Respiratory syncytial virus (RSV) is a leading cause of hospitalization for lower respiratory tract infections amongst infants under 1 year, posing a significant global health challenge. The incidence of RSV exhibits marked seasonality and is influenced by various meteorological...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-02-01
|
| Series: | BioMedical Engineering OnLine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12938-025-01339-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823861711193505792 |
|---|---|
| author | Shuying Wang Yifan Wang Yingxue Zou Cheng-liang Yin |
| author_facet | Shuying Wang Yifan Wang Yingxue Zou Cheng-liang Yin |
| author_sort | Shuying Wang |
| collection | DOAJ |
| description | Abstract Objectives Respiratory syncytial virus (RSV) is a leading cause of hospitalization for lower respiratory tract infections amongst infants under 1 year, posing a significant global health challenge. The incidence of RSV exhibits marked seasonality and is influenced by various meteorological factors, which vary across regions and climates. This study aimed to analyze seasonal trends in RSV-related hospitalization in Tianjin, a region with a semi-arid and semi-humid monsoon climate, and to explore the relationship between these trends and meteorological factors. This research intends to inform RSV prevention strategies, optimize public health policies and medical resource allocation while also promoting vaccine and therapeutic drug development. Methods This study analyzed data from a cohort of 6222 children hospitalized with RSV-related infections. Meteorological data were collected from the Tianjin Binhai International Airport meteorological station, encompassing temperature (℃), air pressure (mmHg), wind speed (m/s), humidity (%), and precipitation (mm). We employed seasonal ARIMA and GAM models to investigate the association between meteorological factors and RSV-related hospitalizations. Results The SARIMA (1,0,0) (0,1,2)12 model effectively predicted RSV-related hospital admissions. Spearman correlation and GAM analysis revealed a significant negative association between the monthly average temperature and RSV hospitalizations. Conclusions Our findings indicated that meteorological factors influence RSV infection-related hospital admissions, with higher monthly average temperatures associated with fewer hospitalizations. The predictive capabilities of the SARIMA model bolster the formulation of targeted RSV prevention strategies, enhancing public health policy and medical resource allocation. Furthermore, continued research into vaccines and therapeutic drugs remains indispensable for augmenting public health outcomes. |
| format | Article |
| id | doaj-art-36421f18447148d79a705b0e3c5e15b4 |
| institution | Kabale University |
| issn | 1475-925X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BioMedical Engineering OnLine |
| spelling | doaj-art-36421f18447148d79a705b0e3c5e15b42025-02-09T12:47:32ZengBMCBioMedical Engineering OnLine1475-925X2025-02-0124111210.1186/s12938-025-01339-yRelationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023Shuying Wang0Yifan Wang1Yingxue Zou2Cheng-liang Yin3Department of Pulmonology, Tianjin Children’s Hospital (Children’s Hospital of Tianjin University)Department of Pulmonology, Tianjin Children’s Hospital (Children’s Hospital of Tianjin University)Department of Pulmonology, Tianjin Children’s Hospital (Children’s Hospital of Tianjin University)Department of Public Health, International College, Krirk UniversityAbstract Objectives Respiratory syncytial virus (RSV) is a leading cause of hospitalization for lower respiratory tract infections amongst infants under 1 year, posing a significant global health challenge. The incidence of RSV exhibits marked seasonality and is influenced by various meteorological factors, which vary across regions and climates. This study aimed to analyze seasonal trends in RSV-related hospitalization in Tianjin, a region with a semi-arid and semi-humid monsoon climate, and to explore the relationship between these trends and meteorological factors. This research intends to inform RSV prevention strategies, optimize public health policies and medical resource allocation while also promoting vaccine and therapeutic drug development. Methods This study analyzed data from a cohort of 6222 children hospitalized with RSV-related infections. Meteorological data were collected from the Tianjin Binhai International Airport meteorological station, encompassing temperature (℃), air pressure (mmHg), wind speed (m/s), humidity (%), and precipitation (mm). We employed seasonal ARIMA and GAM models to investigate the association between meteorological factors and RSV-related hospitalizations. Results The SARIMA (1,0,0) (0,1,2)12 model effectively predicted RSV-related hospital admissions. Spearman correlation and GAM analysis revealed a significant negative association between the monthly average temperature and RSV hospitalizations. Conclusions Our findings indicated that meteorological factors influence RSV infection-related hospital admissions, with higher monthly average temperatures associated with fewer hospitalizations. The predictive capabilities of the SARIMA model bolster the formulation of targeted RSV prevention strategies, enhancing public health policy and medical resource allocation. Furthermore, continued research into vaccines and therapeutic drugs remains indispensable for augmenting public health outcomes.https://doi.org/10.1186/s12938-025-01339-yRespiratory syncytial virus (RSV)SARIMA modelGAM modelMeteorological factors |
| spellingShingle | Shuying Wang Yifan Wang Yingxue Zou Cheng-liang Yin Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023 BioMedical Engineering OnLine Respiratory syncytial virus (RSV) SARIMA model GAM model Meteorological factors |
| title | Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023 |
| title_full | Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023 |
| title_fullStr | Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023 |
| title_full_unstemmed | Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023 |
| title_short | Relationship between RSV-hospitalized children and meteorological factors: a time series analysis from 2017 to 2023 |
| title_sort | relationship between rsv hospitalized children and meteorological factors a time series analysis from 2017 to 2023 |
| topic | Respiratory syncytial virus (RSV) SARIMA model GAM model Meteorological factors |
| url | https://doi.org/10.1186/s12938-025-01339-y |
| work_keys_str_mv | AT shuyingwang relationshipbetweenrsvhospitalizedchildrenandmeteorologicalfactorsatimeseriesanalysisfrom2017to2023 AT yifanwang relationshipbetweenrsvhospitalizedchildrenandmeteorologicalfactorsatimeseriesanalysisfrom2017to2023 AT yingxuezou relationshipbetweenrsvhospitalizedchildrenandmeteorologicalfactorsatimeseriesanalysisfrom2017to2023 AT chengliangyin relationshipbetweenrsvhospitalizedchildrenandmeteorologicalfactorsatimeseriesanalysisfrom2017to2023 |