Evidence map›Paper›PMID 39665781›Full record

Observational studyJMIR public health and surveillance2024

Elevated Ambient Temperature Associated With Reduced Infectious Disease Test Positivity Rates: Retrospective Observational Analysis of Statewide COVID-19 Testing and Weather Across California Counties.

Nicholas Wing-Ping Kwok, Joshua Pevnick, Keith Feldman

Abstract readObservational Study
In one paragraph

Observational study in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nicholas Wing-Ping KwokDepartment of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0009-0006-6724-1513
Joshua PevnickDepartment of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0003-0621-1485
Keith FeldmanDepartment of Pediatrics, Children's Mercy Kansas City, 2401 Gillham Road, Kansas City, MO, 64108, United States, 1 816-302-0512.ORCID 0000-0001-6935-5844

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: From medication usage to the time of day, a number of external factors are known to alter human body temperature (BT), even in the absence of underlying pathology. In select cases, clinical guidance already suggests the consideration of clinical and demographic factors when interpreting BT, such as a decreased threshold for fever as age increases. Recent work has indicated factors impacting BT extend to environmental conditions including ambient temperature. However, the effect sizes of these relationships are often small, and it remains unclear if such relationships result in a meaningful impact on real-world health care practices. Objective: Temperature remains a common element in public health screening efforts. Leveraging the unique testing and reporting infrastructure developed around the COVID-19 pandemic, this paper uses a unique resource of daily-level statewide testing data to assess the relationship between ambient temperatures and positivity rates. As fever was a primary symptom that triggered diagnostic testing for COVID-19, this work hypothesizes that environmentally mediated BT increases would not reflect pathology, leading to decreased COVID-19 test positivity rates as temperature rises. Methods: Statewide COVID-19 polymerase chain reaction testing data curated by the California Department of Public Health were used to obtain the daily number of total tests and positivity rates for all counties across the state. These data were combined with ambient temperature data provided by the National Centers for Environmental Information for a period of 133 days between widespread testing availability and vaccine approval. A mixed-effects beta-regression model was used to estimate daily COVID-19 test positivity rate as a function of ambient temperature, population, and estimates of COVID prevalence, with nested random effects for a day of the week within unique counties across the state. Results: Considering over 19 million tests performed over 4 months and across 45 distinct counties, adjusted model results highlighted a significant negative association between daily ambient temperature and testing positivity rate (P<.001). Results of the model are strengthened as, using the same testing data, this relationship was not present in a sensitivity analysis using random daily temperatures drawn from the range of observed values (P=.52). Conclusions: These results support the underlying hypothesis and demonstrate the relationship between environmental factors and BT can impact an essential public health activity. As health care continues to operate using thresholds of BT as anchor points (ie, ≥100.4 as fever) it is increasingly important to develop approaches to integrate the array of factors known to influence BT measurement. Moreover, as weather data are not often readily available in the same systems as patient data, these findings present a compelling case for future research into when and how environmental context can best be used to improve the interpretation of patient data.

Indexed as

COVID-19COVID-19 TestingWeatherCaliforniaFeverHot TemperatureHumansRetrospective StudiesTemperatureambient temperaturebody temperatureBTcoronavirusCOVID-19COVID-19 pandemicdiagnosticsdiagnostic testdiagnostic testingenvironmentenvironmentalenvironmental contextenvironmental factorfebrilefeverfeverishinfectiouspandemicpublic health surveillancepulmonaryrespiratorySARS-CoV-2

Identifiers

PMID39665781
PMCPMC11656991

What OpenQuestion holds

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Registered trials

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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.