ArticlePLoS computational biology2017
The use of ambient humidity conditions to improve influenza forecast.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using internet-based query and climate data to predict climate-sensitive infectious disease risks: a systematic review of epidemiological evidence.International journal of biometeorology · 2021Pooled it
- Improving influenza forecast in the tropics and subtropics: a case study of Hong Kong.Journal of the Royal Society, Interface · 2025Article
- Inference of transmission dynamics and retrospective forecast of invasive meningococcal disease.PLoS computational biology · 2023Article
- Development of Accurate Long-lead COVID-19 Forecast.PLoS computational biology · 2023Article
- Using real-time data to guide decision-making during an influenza pandemic: A modelling analysis.PLoS computational biology · 2023Article
- Spatial Variation in Humidity and the Onset of Seasonal Influenza Across the Contiguous United States.GeoHealth · 2022Article
- Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic.Scientific reports · 2021Article
- Role of meteorological factors in the transmission of SARS-CoV-2 in the United States.Nature communications · 2021Article
- Role of air temperature and humidity in the transmission of SARS-CoV-2 in the United States.medRxiv : the preprint server for health sciences · 2020Article
- The delayed effect of wildfire season particulate matter on subsequent influenza season in a mountain west region of the USA.Environment international · 2020Article
- FluSense: A Contactless Syndromic Surveillance Platform for Influenza-Like Illness in Hospital Waiting Areas.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2020Article
- Development and validation of influenza forecasting for 64 temperate and tropical countries.PLoS computational biology · 2019Article
- Evaluation of mechanistic and statistical methods in forecasting influenza-like illness.Journal of the Royal Society, Interface · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.