Epidemiologic surveillance for controlling Covid-19 pandemic: types, challenges and implications

Abstract

The objectives of the study was to determine the types, challenges and implications of surveillance methods for controlling Covid-19 pandemic. An integrative article review was done. The source of data were documents from WHO, Euro-surveillance, CDC, Saudi CDC, MOH, and journals from PubMed, Medline, etc. The inclusion searching criteria were surveillance, Covid-19, types, benefits and challenges, during the period 2005−2020. Published studies, reviews and guidelines that determined these criteria were collected. Data extraction and analysis were completed for all included articles. A critical appraisal was done based on the University of Michigan Practice Guideline’s levels of evidence. The final sample for the integrative review comprised 30 studies. Results revealed that types of Covid-9 surveillance includes routine surveillance (comprehensive, case-based, and aggregated weakly methods), active, wildlife, syndromic, sentinel and sentinel-syndromic methods. Laboratory and hospital-based surveillance are another important types. Help-lines, surveys, participatory electronic, digital and event-based surveillance are relatively new cost-effective methods. Many surveillance indicators can be calculated. Timely and accurate of surveillance data is an essential element for effective Covid-19 interventions. Regarding challenges, the quality of surveillance in developing countries is constrained by resources and training. The main limitations of surveillance are under-ascertainment/under-reporting, lack of timeliness and completeness of surveillance data. In conclusion, surveillance is a cornerstones for controlling Covid-19 pandemic. Enhancing Covid-19 surveillance is vital for rapid cases detection, containing spread & ending pandemic.

Medical students’ acceptance and perceptions of e-learning during the Covid-19 closure time in King Abdulaziz University, Jeddah

“…Nowadays, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causing Covid-19, is one of the most aggressive and deadly infectious diseases [ 1 ]. SARS-CoV-2 was classified as a pathogen with Risk Group 3 as it carries considerable risk to the community due to its effect on life, health, and the global economy [ 2 ]. Covid-19 has been declared as a pandemic disease by the WHO on March 11th, 2020 [ 2 , 3 ].…”

“…SARS-CoV-2 was classified as a pathogen with Risk Group 3 as it carries considerable risk to the community due to its effect on life, health, and the global economy [ 2 ]. Covid-19 has been declared as a pandemic disease by the WHO on March 11th, 2020 [ 2 , 3 ]. The rapidly evolving global pandemic has affected almost all systems during this crisis [ 4 ].…”

Effect of preventive measures in the containment of SARS-CoV-2 epidemic: a comparative study

“…The data used for the present study refer to pandemic country statistics from 21 February to 6 October 2020, retrieved from COVID-19 World Statistics Data.The reliability of the data depends on the country's ability to track infected people, collect and analyze the samples and record the death as argued by (Ibrahim, 2020;Lu et al, 2020). The identification of individuals for testing against contamination by COVID19 is guided by the WHO protocols, which establishes the mandatory testing of people with symptoms, and the contacts of infected people.…”

Evaluating COVID-19 reporting data in the context of testing strategies across 31 LMICs

“…Existing efforts to evaluate LMIC surveillance systems, however, are largely qualitative, country-specific, or based on commentary. [4][5][6] Further, most national-level studies of NPI impacts focus on high-income countries, [7][8][9][10][11] but there is evidence that these insights cannot be readily generalized to LMIC settings. 12,2 This leaves an important knowledge gap in understanding how to evaluate and interpret COVID-19 epidemiological data from LMICs.…”