Dataset Information

Defining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries.

ABSTRACT:

Background

Respiratory syncytial virus (RSV) infections are one of the leading causes of lower respiratory tract infections and have a major burden on society. For prevention and control to be deployed effectively, an improved understanding of the seasonality of RSV is necessary.

Objectives

The main objective of this study was to contribute to a better understanding of RSV seasonality by examining the GERi multi-country surveillance dataset.

Methods

RSV seasons were included in the analysis if they contained ≥100 cases. Seasonality was determined using the "average annual percentage" method. Analyses were performed at a subnational level for the United States and Brazil.

Results

We included 601 425 RSV cases from 12 countries. Most temperate countries experienced RSV epidemics in the winter, with a median duration of 10-21 weeks. Not all epidemics fit this pattern in a consistent manner, with some occurring later or in an irregular manner. More variation in timing was observed in (sub)tropical countries, and we found substantial differences in seasonality at a subnational level. No association was found between the timing of the epidemic and the dominant RSV subtype.

Conclusions

Our findings suggest that geographical location or climatic characteristics cannot be used as a definitive predictor for the timing of RSV epidemics and highlight the need for (sub)national data collection and analysis.

SUBMITTER: Staadegaard L

PROVIDER: S-EPMC8542954 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Publications

Defining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries.

Staadegaard Lisa L Caini Saverio S Wangchuk Sonam S Thapa Binay B de Almeida Walquiria Aparecida Ferreira WAF de Carvalho Felipe Cotrim FC Fasce Rodrigo A RA Bustos Patricia P Kyncl Jan J Novakova Ludmila L Caicedo Alfredo Bruno AB de Mora Coloma Domenica Joseth DJ Meijer Adam A Hooiveld Mariëtte M Huang Q Sue QS Wood Tim T Guiomar Raquel R Rodrigues Ana Paula AP Lee Vernon Jian Ming VJM Ang Li Wei LW Cohen Cheryl C Moyes Jocelyn J Larrauri Amparo A Delgado-Sanz Concepción C Demont Clarisse C Bangert Mathieu M Dückers Michel M van Summeren Jojanneke J Paget John J

Influenza and other respiratory viruses 20210713 6

<h4>Background</h4>Respiratory syncytial virus (RSV) infections are one of the leading causes of lower respiratory tract infections and have a major burden on society. For prevention and control to be deployed effectively, an improved understanding of the seasonality of RSV is necessary.<h4>Objectives</h4>The main objective of this study was to contribute to a better understanding of RSV seasonality by examining the GERi multi-country surveillance dataset.<h4>Methods</h4>RSV seasons were include ...[more]

PMID: 34255934

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Project description:IntroductionRespiratory syncytial virus (RSV) is a primary source of acute lower respiratory tract infection, the leading cause of death in children under 5. Over 99% of RSV-attributed deaths occur in low-income countries, including Madagascar. RSV transmission is linked to climate, driving highly seasonal dynamics.MethodsWe used generalised additive models (GAMs) to identify correlates of reported RSV infections in Antananarivo, Madagascar, from January 2011 to December 2021, then fit catalytic models to cumulative age-structured incidence to estimate age-specific force of infection (FOI). We fit a time-series susceptible-infected-recovered (TSIR) model to the dataset to estimate weekly RSV transmission, then evaluated associations with precipitation, humidity and temperature using generalised linear models. We used GAMs to quantify interannual trends in climate and assess whether significant deviations in RSV burden occurred in years representing climatic anomalies.ResultsReported RSV infections in Antananarivo were significantly associated with patients aged ≤2 years. Highest FOI was estimated in patients aged ≤1 year, with transmission declining to near-zero by age 5 before rising in older (60+) cohorts. TSIR models estimated a January to February peak in RSV transmission, which was strongly positively associated with precipitation and more weakly with temperature but negatively related to relative humidity. Precipitation, humidity and temperature all increased across the study period in Antananarivo, while reported RSV infections remained stable. Significant deviations in RSV burden were not associated with clear climate anomalies.ConclusionsStable rates of reported RSV infections in Antananarivo across the past decade may reflect contrasting impacts of elevated precipitation and increased humidity on transmission. If future climate changes yield more rapidly accelerating precipitation than humidity, this could accelerate RSV burden. Introduction of recently developed public health interventions to combat RSV in low-income settings like Madagascar is essential to mitigating disease burden, in particular to combat any future climate-driven increases in transmission or severity.

Project description:BackgroundThere is currently no standard way of defining malaria seasonality, resulting in a wide range of definitions reported in the literature. Malaria cases show seasonal peaks in most endemic settings, and the choice and timing for optimal malaria control may vary by seasonality. A simple approach is presented to describe the seasonality of malaria, to aid localized policymaking and targeting of interventions.MethodsA series of systematic literature reviews were undertaken to identify studies reporting on monthly data for full calendar years on clinical malaria, hospital admission with malaria and entomological inoculation rates (EIR). Sites were defined as having 'marked seasonality' if 75% or more of all episodes occurred in six or less months of the year. A 'concentrated period of malaria' was defined as the six consecutive months with the highest cumulative proportion of cases. A sensitivity analysis was performed based on a variety of cut-offs.ResultsMonthly data for full calendar years on clinical malaria, all hospital admissions with malaria, and entomological inoculation rates were available for 13, 18, and 11 sites respectively. Most sites showed year-round transmission with seasonal peaks for both clinical malaria and hospital admissions with malaria, with a few sites fitting the definition of 'marked seasonality'. For these sites, consistent results were observed when more than one outcome or more than one calendar year was available from the same site. The use of monthly EIR data was found to be of limited value when looking at seasonal variations of malaria transmission, particularly at low and medium intensity levels.ConclusionThe proposed definition discriminated well between studies with 'marked seasonality' and those with less seasonality. However, a poor fit was observed in sites with two seasonal peaks. Further work is needed to explore the applicability of this definition on a wide-scale, using routine health information system data where possible, to aid appropriate targeting of interventions.

Dataset Information

Defining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries.

Background

Objectives

Methods

Results

Conclusions

Publications

Defining the seasonality of respiratory syncytial virus around the world: National and subnational surveillance data from 12 countries.

Similar Datasets

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