Evidence map›Paper›PMID 37027359›Full record

ArticlePloS one2023

Transmission dynamics and baseline epidemiological parameter estimates of Coronavirus disease 2019 pre-vaccination: Davao City, Philippines.

Loreniel E Añonuevo, Zython Paul T Lachica, Deza A Amistas, Jayve Iay E Lato, Hanna Lyka C Bontilao, Jolly Mae G Catalan, Rachel Joy F Pasion, Annabelle P Yumang, Alexis Erich S Almocera, Jayrold P Arcede and 2 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Loreniel E AñonuevoCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
Zython Paul T LachicaCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
Deza A AmistasCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
Jayve Iay E LatoCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
Hanna Lyka C BontilaoCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
Jolly Mae G CatalanDepartment of Health - Davao Center for Health Development, Davao City, Philippines.
Rachel Joy F PasionDepartment of Health - Davao Center for Health Development, Davao City, Philippines.
Annabelle P YumangDepartment of Health - Davao Center for Health Development, Davao City, Philippines.
Alexis Erich S AlmoceraCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
Jayrold P ArcedeCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.
May Anne E MataCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.ORCID 0000-0002-2967-344X
Aurelio A de Los Reyes VCenter for Applied Modeling Data, Analytics, and Bioinformatics for Decision Support Systems in Health, University of the Philippines Mindanao, Davao City, Philippines.ORCID 0000-0001-5418-4579

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Coronavirus disease 2019 (COVID-19) has exposed many systemic vulnerabilities in many countries' health system, disaster preparedness, and adequate response capabilities. With the early lack of data and information about the virus and the many differing local-specific factors contributing to its transmission, managing its spread had been challenging. The current work presents a modified Susceptible-Exposed-Infectious-Recovered compartmental model incorporating intervention protocols during different community quarantine periods. The COVID-19 reported cases before the vaccine rollout in Davao City, Philippines, are utilized to obtain baseline values for key epidemiologic model parameters. The probable secondary infections (i.e., time-varying reproduction number) among other epidemiological indicators were computed. Results show that the cases in Davao City were driven by the transmission rates, positivity proportion, latency period, and the number of severely symptomatic patients. This paper provides qualitative insights into the transmission dynamics of COVID-19 along with the government's implemented intervention protocols. Furthermore, this modeling framework could be used for decision support, policy making, and system development for the current and future pandemics.

Indexed as

COVID-19HumansPhilippinesQuarantineSARS-CoV-2Vaccination

Identifiers

PMID37027359
PMCPMC10081793

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.