Evidence map›Paper›PMID 37610119›Full record

ArticlePublic health reports (Washington, D.C. : 1974)

Recent Advances in the Use of the Mortality Syndromic Surveillance System-New York City, 2015-2020.

Alejandro F Castro, Wenhui Li, Blanca Bernard-Davila, Mary Huynh, Gretchen Van Wye

Open access · greenAbstract read
In one paragraph

Article in Public health reports (Washington, D.C. : 1974). 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
0.4field-weighted citation impact, top 33% of its field
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, 2 citations in OpenAlex.

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

5 authors at 1 institution in 1 country.

Alejandro F CastroBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, NY, USA.ORCID 0000-0002-9241-5902
Wenhui LiBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, NY, USA.
Blanca Bernard-DavilaBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, NY, USA.
Mary HuynhBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, NY, USA.
Gretchen Van WyeBureau of Vital Statistics, New York City Department of Health and Mental Hygiene, New York, NY, USA.
New York City Department of Health and Mental Hygiene · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveNew York City's automated mortality syndromic surveillance system monitors temporal and spatial patterns in mortality. To describe the use of the syndromic surveillance system, we used the system to find mortality patterns for the 15 leading causes of death and for deaths from rare and reportable diseases in New York City from February 2015 through June 2020. We used results to find aberrations that indicate threats to public health.

methodsWe used unobserved components models to analyze time series of mortality counts for leading causes of death, historical limits methods for rare and reportable diseases, and SaTScan for temporal-spatial cluster analysis. We obtained data on the number of deaths from the electronic death registry system maintained by the city's Bureau of Vital Statistics.

resultsThe mortality syndromic surveillance system detected an increase in the number of deaths from heart disease by April 1, 2020, when 75.0 deaths occurred on March 24, 2020, instead of an expected 45.8 deaths (95% upper prediction limit of 61.0) and an increase in the number of deaths from all causes on March 20, 2020, when 194.0 deaths were observed while 150.1 deaths were expected (95% upper prediction limit of 178.0). The number of deaths from all causes returned to normal the week beginning June 14, 2020, when 990.0 deaths were observed and 998.8 deaths were expected. PRACTICE IMPLICATIONS: When compared with efforts from New York City to provide yearly vital statistics, the automated mortality syndromic surveillance system can provide timely mortality data with fewer resources and raise the capacity to detect anomalous increases in mortality.

Indexed as

Cause of DeathPopulation SurveillanceHumansMortalityNew York Cityepidemiologyforecastingmortalitysurveillance

Identifiers

PMID37610119
PMCPMC11037230
OpenAlexW4386084475

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.