scholarly journals Population surveillance approach to detect and respond to new clusters of COVID-19

2021 ◽  
Vol 47 (56) ◽  
pp. 243-250
Author(s):  
Erin E Rees ◽  
Rachel Rodin ◽  
Nicholas H Ogden
Keyword(s):  
Sample Size ◽  
Unit Area ◽  
Respiratory Illness ◽  
Threshold Level ◽  
Population Surveillance ◽  
Sample Size Determination ◽  
Virus Infections ◽  
Surveillance Strategy ◽  
Prevalence Level ◽  
Target Prevalence

Background: To maintain control of the coronavirus disease 2019 (COVID-19) epidemic as lockdowns are lifted, it will be crucial to enhance alternative public health measures. For surveillance, it will be necessary to detect a high proportion of any new cases quickly so that they can be isolated, and people who have been exposed to them traced and quarantined. Here we introduce a mathematical approach that can be used to determine how many samples need to be collected per unit area and unit time to detect new clusters of COVID-19 cases at a stage early enough to control an outbreak. Methods: We present a sample size determination method that uses a relative weighted approach. Given the contribution of COVID-19 test results from sub-populations to detect the disease at a threshold prevalence level to control the outbreak to 1) determine if the expected number of weekly samples provided from current healthcare-based surveillance for respiratory virus infections may provide a sample size that is already adequate to detect new clusters of COVID-19 and, if not, 2) to determine how many additional weekly samples were needed from volunteer sampling. Results: In a demonstration of our method at the weekly and Canadian provincial and territorial (P/T) levels, we found that only the more populous P/T have sufficient testing numbers from healthcare visits for respiratory illness to detect COVID-19 at our target prevalence level—assumed to be high enough to identify and control new clusters. Furthermore, detection of COVID-19 is most efficient (fewer samples required) when surveillance focuses on healthcare symptomatic testing demand. In the volunteer populations: the higher the contact rates; the higher the expected prevalence level; and the fewer the samples were needed to detect COVID-19 at a predetermined threshold level. Conclusion: This study introduces a targeted surveillance strategy, combining both passive and active surveillance samples, to determine how many samples to collect per unit area and unit time to detect new clusters of COVID-19 cases. The goal of this strategy is to allow for early enough detection to control an outbreak.

Perceived Influence of Students’ Demographic Variables on Their Access to Financial Aids in Public Universities in Rivers State, Nigeria

2018 ◽  
Vol 8 (2) ◽  
pp. 32-50
Author(s):  
Emmanuel Olorunleke Eseyin
Keyword(s):  
Sample Size ◽  
Public Universities ◽  
Sampling Technique ◽  
Demographic Variables ◽  
Sample Size Determination ◽  
Interview Schedule ◽  
The Public ◽  
Research Questions ◽  
Level Of Significance ◽  
Rivers State

The paper investigated the perceived influence of students’ demographic variables on their access to financial aids in public Universities in Rivers State, Nigeria. Six questions were formulated to guide the study and five hypotheses tested at 0.05 level of significance. The design adopted for the study was an analytical survey. The population of the study included 78, 216 students (34,997 male and 43,219 female) in the three public Universities in Rivers State. The sample of the study covered 791 students (Male= 395 and Female= 396) selected through the random sampling technique while Taro Yamane method of sample size determination was used for determining the sample size. The instruments used for collecting responses from students were questionnaire and a ten items interview schedule. The research questions were answered using frequency, percentage and cumulative percentage. Findings of the study revealed that students’ demographic variables have an influence on their access to financial aids in public Universities in Rivers State, Nigeria. The implication of this is that the government’s expenditure on education will continue to increase in the absence of these alternative financial aids in the public Universities in Rivers State, Nigeria.

scholarly journals Exit strategies: optimising feasible surveillance for detection, elimination, and ongoing prevention of COVID-19 community transmission

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
K. Lokuge ◽  
E. Banks ◽  
S. Davis ◽  
L. Roberts ◽  
T. Street ◽  
...  
Keyword(s):  
Early Detection ◽  
Respiratory Symptoms ◽  
Respiratory Illness ◽  
Reproductive Number ◽  
Surveillance Strategy ◽  
Transmission Chain ◽  
Containment Measures ◽  
Testing Uptake ◽  
Community Transmission

Abstract Background Following implementation of strong containment measures, several countries and regions have low detectable community transmission of COVID-19. We developed an efficient, rapid, and scalable surveillance strategy to detect remaining COVID-19 community cases through exhaustive identification of every active transmission chain. We identified measures to enable early detection and effective management of any reintroduction of transmission once containment measures are lifted to ensure strong containment measures do not require reinstatement. Methods We compared efficiency and sensitivity to detect community transmission chains through testing of the following: hospital cases; fever, cough and/or ARI testing at community/primary care; and asymptomatic testing; using surveillance evaluation methods and mathematical modelling, varying testing capacities, reproductive number (R) and weekly cumulative incidence of COVID-19 and non-COVID-19 respiratory symptoms using data from Australia. We assessed system requirements to identify all transmission chains and follow up all cases and primary contacts within each chain, per million population. Results Assuming 20% of cases are asymptomatic and 30% of symptomatic COVID-19 cases present for testing, with R = 2.2, a median of 14 unrecognised community cases (8 infectious) occur when a transmission chain is identified through hospital surveillance versus 7 unrecognised cases (4 infectious) through community-based surveillance. The 7 unrecognised community upstream cases are estimated to generate a further 55–77 primary contacts requiring follow-up. The unrecognised community cases rise to 10 if 50% of cases are asymptomatic. Screening asymptomatic community members cannot exhaustively identify all cases under any of the scenarios assessed. The most important determinant of testing requirements for symptomatic screening is levels of non-COVID-19 respiratory illness. If 4% of the community have respiratory symptoms, and 1% of those with symptoms have COVID-19, exhaustive symptomatic screening requires approximately 11,600 tests/million population using 1/4 pooling, with 98% of cases detected (2% missed), given 99.9% sensitivity. Even with a drop in sensitivity to 70%, pooling was more effective at detecting cases than individual testing under all scenarios examined. Conclusions Screening all acute respiratory disease in the community, in combination with exhaustive and meticulous case and contact identification and management, enables appropriate early detection and elimination of COVID-19 community transmission. An important component is identification, testing, and management of all contacts, including upstream contacts (i.e. potential sources of infection for identified cases, and their related transmission chains). Pooling allows increased case detection when testing capacity is limited, even given reduced test sensitivity. Critical to the effectiveness of all aspects of surveillance is appropriate community engagement, messaging to optimise testing uptake and compliance with other measures.

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