The Epidemiology Characteristics of Positive COVID-19 patients in a Caribbean Territory

  1. Chavin D. Gopaul
  2. Dale Ventour
  3. Michelle Trotman
  4. Davlin Thomas

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Abstract

Background

The purpose of the study is to determine the epidemiology of COVID-19 in a Caribbean Territory by the characterisation of patients in terms of, the numbers, socio demographics and associated co-morbidities. This comparison was done between local cases and imported cases. There have been no prior studies on COVID-19 in the Caribbean and as such this paper attempts to discuss the patterns associated with COVID-19 patients in the Caribbean.

Methods

This study determined the epidemiology of COVID-19 in a Caribbean territory using retrospective data. Analysis was performed using Excel and SPSS 22.0.

Results

The majority of patients were female (61.9%) vs male (38.0%). The majority of the population were between 45 -64 yrs (43.4%) followed by above 65 at 28.8%. Cough was the most common presenting complaint at 44.9%, with fever being second 37.1%. The majority of female participants had a travel history at 61.9%, while males were 38.0 %. The occurrence of cough was high among both local cases (46.4%) and imported cases (47.6%).

Conclusions

These patterns can inform clinicians and other health care workers on the unique findings associated with COVID-19 positive patients especially those in the Caribbean region

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  1. ScreenIT

    SciScore for 10.1101/2020.08.06.20148288: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    2.2 Statistical Analysis: All statistical analysis was processed using IBM SPSS 22.0 statistical software.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are various limitations that need to be taken into account when interpreting the findings of this study. As mentioned above, the sample used in this study did not have an equal number of male and female patients, which limited the assessment of the effect of gender on comorbidities and symptoms. Despite the highlighted limitation, the obtained findings give important insights into the epidemiology of COVID-19 patients in the Caribbean. The study raises questions over the distribution of the infections across the gender groups, which needs to be further analyzed by future researchers. The study also singles out individuals who have hypertension and DM to be at the highest risk for COVID-19 infection. The disease prevention strategies should, therefore, focus on limiting the exposure of the identified groups to the disease as well as other public measures which include containment of positive patients, social distancing, proper hand hygiene and the use of face masks (17, 21, 22). Based on the obtained outcome, there is a need to identify dry cough and fever as the main symptoms in the identification of patients infected with COVID-19.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.08.06.20148288v1 on medRxiv