SARS-CoV-2 Antibody Seroprevalence in Wuhan, China, from 23 April to 24 May 2020

ABSTRACT The outbreak of coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China, in December 2019. To investigate the prevalence of COVID-19 in Wuhan, we conducted serologic tests on 35,326 individuals from four different communities to estimate cumulative incidence of infection. Our results showed that 1,332 individuals (3.77%) showed positive COVID-19 antibody (either IgM or IgG). Males had a lower positivity rate than females (3.02% versus 4.52%). The antibody positivity rates showed a clear trend of increase according to patients’ ages and varied among different communities. The results indicate that public health interventions may play important roles in the control of COVID-19. IMPORTANCE Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China. Afterwards, a number of public health interventions were implemented, including lock-down, face mask ordinances, and social distancing. Studies that rely on viral RNA testing of symptomatic patients have shown that these multifaceted interventions contributed to the control of the COVID-19 outbreak in Wuhan and delayed the epidemic’s progression. However, these estimates of confirmed cases may miss large numbers of asymptomatic patients and recovered symptomatic patients who were not tested. To investigate the prevalence of COVID-19 in Wuhan, we conducted serologic tests on 35,326 individuals to estimate the cumulative incidence of infection. The results suggest that public health interventions may play important roles in the control of COVID-19.

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A comparison of Passive Surveillance and Active Cluster-Based Surveillance for Dengue Fever in southern coastal Ecuador

10.21203/rs.3.rs-17173/v2 ◽

2020 ◽

Author(s):

Melissa Vitale ◽

Christina Lupone ◽

Aileen Kenneson-Adams ◽

Robinson Jaramillo Ochoa ◽

Tania Ordoñez ◽

...

Keyword(s):

Public Health ◽

Cumulative Incidence ◽

Complex Disease ◽

Health Interventions ◽

Outbreak Detection ◽

Mosquito Vector ◽

Disease Dynamics ◽

Passive Surveillance ◽

Public Health Interventions ◽

Chi Square

Abstract Background: Dengue is a major emerging infectious disease, endemic throughout the tropics and subtropics, with approximately 2.5 billion people at risk globally. Active (AS) and passive surveillance (PS), when combined, can improve our understanding of dengue’s complex disease dynamics to guide effective, targeted public health interventions. The objective of this study was to compare findings from the Ministry of Health (MoH) PS to a prospective AS arbovirus research study in Machala, Ecuador in 2014 and 2015[P1] . Methods: Dengue cases in the PS system were compared to laboratory confirmed acute dengue illness cases that entered the AS study during the study period. Variables of interest included age, class, and sex. Outbreak detection curves by epidemiologic week, overall cumulative incidence and age-specific incidence proportions were calculated. Descriptive statistics were tabulated for all variables of interest. Chi-square tests were performed to compare demographic characteristics between the AS and PS data sets in 2014 and 2015. Results: 177 and 245 cases were identified from 1/1/2014 to 12/31/2015 by PS and AS, respectively; nine cases appeared in both systems. AS identified a greater number of laboratory-confirmed cases in 2014, accounting for more than 60% of dengue cases in the study area. In 2015, the opposite trend was observed with PS identifying 60% of the dengue cases in the region. Peak transmission time, as noted by AS and PS was similar in 2014 whereas earlier detection was observed by AS in 2015.Younger patients were more frequently identified by PS, while older patients were identified more frequently by AS. The cumulative incidence proportion for laboratory confirmed dengue illness reported via PS to the MoH was 4.12 cases per 10,000 residents in 2014, and 2.21 cases per 10,000 residents in 2015.Conclusions: Each surveillance system captured distinct demographic subgroups within the Machala population, possibly due to differences in healthcare seeking behaviors, access to care, emerging threats of other viruses transmitted by the same mosquito vector and/or differences in clinical presentation. Integrating AS with pre-existing PS can aid in identifying additional cases in previously under diagnosed subpopulations, improving our understanding of disease dynamics, and facilitating the implementation of timely public health interventions.

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COVID-19: underpowered randomised trials, or no randomised trials?

Trials ◽

10.1186/s13063-021-05209-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Atle Fretheim

Keyword(s):

Public Health ◽

Sample Size ◽

Systematic Reviews ◽

Sample Size Calculation ◽

Scientific Progress ◽

Face Mask ◽

Health Interventions ◽

Randomised Trials ◽

Public Health Interventions ◽

Key Barrier

AbstractA recently published trial of face mask use to protect against COVID-19 demonstrated a key barrier to carrying out randomised trials in public health: the need for unattainably large sample sizes. For many public health interventions, the choice is not between sufficiently powered trials and underpowered trials, but between underpowered trials and no trials at all. Underpowered trials should be viewed as contributions to the larger body of evidence, alongside other studies of various sizes and designs, collectively assessed and synthesized in systematic reviews. Overemphasis on sample size calculation is probably more of a hindrance than a help to scientific progress.

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Knowledge and Determinants of Behavioral Responses to the Pandemic of COVID-19

Frontiers in Medicine ◽

10.3389/fmed.2021.673187 ◽

2021 ◽

Vol 8 ◽

Author(s):

Gang Lv ◽

Jing Yuan ◽

Stephanie Hsieh ◽

Rongjie Shao ◽

Minghui Li

Keyword(s):

Public Health ◽

Health Behaviors ◽

Self Efficacy ◽

Behavioral Responses ◽

Face Mask ◽

Preventive Health ◽

Health Interventions ◽

Public Health Interventions ◽

Social Distancing ◽

Preventive Health Behaviors

Background: Understanding knowledge and behavioral responses to the pandemic of coronavirus disease 2019 (COVID-19) is important for appropriate public health interventions.Objectives: To assess knowledge of COVID-19 and to examine determinants associated with the adoption of preventive health behaviors among future health care providers.Methods: An anonymous online survey was sent out to pharmacy students in high and low-endemic areas of COVID-19 in China. Based on recommendations from the Chinese Center for Disease Control and Prevention, preventive health behaviors examined in this study included washing hands, wearing a face mask, and maintaining social distancing. The Health Belief Model (HBM) was used and measured by a seven-point Likert scale (one as extremely unlikely; seven as extremely likely). Multivariate linear regression models were used to examine predictors of preventive health behaviors.Results: Among 203 respondents who finished the survey, a medium level of knowledge (4.41 ± 0.95) of COVID-19 was reported. Respondents were extremely likely to wear a face mask (6.85 ± 0.60), but only moderately likely to engage in washing hands (5.95 ± 1.38) and maintaining social distancing (6.19 ± 1.60). Determinants of washing hands were cue to action, self-efficacy, knowledge, and gender; wearing a face mask were cue to action, self-efficacy, knowledge, and ethnicity; and maintaining social distancing were cue to action and self-efficacy.Conclusions: Public health interventions should consider incorporating cue to action, self-efficacy, and knowledge as factors to potentially improve the adoption of face mask-wearing, hand washing, and social distancing as appropriate individual preventive measures, especially if local and regional authorities are considering reopening schools sometime in future.

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A comparison of Passive Surveillance and Active Cluster-Based Surveillance for Dengue Fever in southern coastal Ecuador

10.21203/rs.3.rs-17173/v3 ◽

2020 ◽

Author(s):

Melissa Vitale ◽

Christina D Lupone ◽

Aileen Kenneson-Adams ◽

Robinson Jaramillo Ochoa ◽

Tania Ordoñez ◽

...

Keyword(s):

Public Health ◽

Cumulative Incidence ◽

Complex Disease ◽

Health Interventions ◽

Outbreak Detection ◽

Mosquito Vector ◽

Disease Dynamics ◽

Passive Surveillance ◽

Public Health Interventions ◽

Chi Square

Abstract Background: Dengue is a major emerging infectious disease, endemic throughout the tropics and subtropics, with approximately 2.5 billion people at risk globally. Active (AS) and passive surveillance (PS), when combined, can improve our understanding of dengue’s complex disease dynamics to guide effective, targeted public health interventions. The objective of this study was to compare findings from the Ministry of Health (MoH) PS to a prospective AS arbovirus research study in Machala, Ecuador in 2014 and 2015. Methods: Dengue cases in the PS system were compared to laboratory confirmed acute dengue illness cases that entered the AS study during the study period. Variables of interest included age, class, and sex. Outbreak detection curves by epidemiologic week, overall cumulative incidence and age-specific incidence proportions were calculated. Descriptive statistics were tabulated for all variables of interest. Chi-square tests were performed to compare demographic characteristics between the AS and PS data sets in 2014 and 2015. Results: 177 and 245 cases were identified from 1/1/2014 to 12/31/2015 by PS and AS, respectively; nine cases appeared in both systems. AS identified a greater number of laboratory-confirmed cases in 2014, accounting for more than 60% of dengue cases in the study area. In 2015, the opposite trend was observed with PS identifying 60% of the dengue cases in the region. Peak transmission time, as noted by AS and PS was similar in 2014 whereas earlier detection was observed by AS in 2015.Younger patients were more frequently identified by PS, while older patients were identified more frequently by AS. The cumulative incidence proportion for laboratory confirmed dengue illness reported via PS to the MoH was 4.12 cases per 10,000 residents in 2014, and 2.21 cases per 10,000 residents in 2015.Conclusions: Each surveillance system captured distinct demographic subgroups within the Machala population, possibly due to differences in healthcare seeking behaviors, access to care, emerging threats of other viruses transmitted by the same mosquito vector and/or differences in clinical presentation. Integrating AS with pre-existing PS can aid in identifying additional cases in previously under diagnosed subpopulations, improving our understanding of disease dynamics, and facilitating the implementation of timely public health interventions..

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Comparison of Active and Passive Surveillance of Dengue in Machala, Ecuador

10.21203/rs.3.rs-17173/v1 ◽

2020 ◽

Author(s):

Melissa Vitale ◽

Christina Lupone ◽

Aileen Kenneson-Adams ◽

Robinson Jaramillo Ochoa ◽

Tania Ordoñez ◽

...

Keyword(s):

Public Health ◽

Cumulative Incidence ◽

Complex Disease ◽

Health Interventions ◽

Outbreak Detection ◽

Mosquito Vector ◽

Disease Dynamics ◽

Passive Surveillance ◽

Public Health Interventions ◽

Chi Square

Abstract Dengue is a major emerging infectious disease, endemic throughout the tropics and subtropics, with approximately 2.5 billion people at risk globally. Active (AS) and passive surveillance (PS), when combined, can improve our understanding of dengue’s complex disease dynamics to guide effective, targeted public health interventions. The objective of this study was to compare findings from the Ministry of Health (MoH) PS to a prospective AS arbovirus research study in Machala, Ecuador from 2014-2015. Dengue cases in the PS system were compared to laboratory confirmed acute dengue illness cases that entered the AS study during the study period. Variables of interest included age, class, and sex. Outbreak detection curves by epidemiologic week, overall cumulative incidence and age-specific incidence proportions were calculated. Descriptive statistics were tabulated for all variables of interest. Chi-square tests were performed to compare demographic characteristics between the AS and PS data sets in 2014 and 2015. 177 and 245 cases were identified from January 1, 2014 to December 31, 2015 by PS and AS, respectively; nine cases appeared in both systems. AS identified a greater number of laboratory-confirmed cases in 2014, accounting for more than 60% of dengue illness cases in the study area. In 2015, the opposite trend was observed with PS identifying 60% of the dengue illness cases in the region. Younger patients were more frequently identified by PS, while older patients were identified more frequently by AS. The cumulative incidence proportion for laboratory confirmed dengue illness reported via PS to the MoH was 4.12 cases per 10,000 Machala residents in 2014, and 2.21 cases per 10,000 Machala residents in 2015. Each surveillance system captured different demographic subgroups within the Machala population, possibly due to differences in healthcare seeking behaviors, access to care, emerging threats of other viruses transmitted by the same mosquito vector and/or differences in clinical presentation due to changes in the predominant dengue serotype in circulation. Integrating AS with pre-existing PS can aid in identifying additional cases in previously under diagnosed subpopulations, improving our understanding of disease dynamics, and facilitating the implementation of public health interventions to reduce the burden of disease.

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Descriptive, Retrospective Study of the Clinical Characteristics of Asymptomatic COVID-19 Patients

mSphere ◽

10.1128/msphere.00922-20 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Huan Han ◽

Zaichao Xu ◽

Xiaoming Cheng ◽

Youquan Zhong ◽

Li Yuan ◽

...

Keyword(s):

Public Health ◽

Clinical Characteristics ◽

Interleukin 2 ◽

Virus Transmission ◽

Normal Liver ◽

Health Interventions ◽

Public Health Interventions ◽

Cell Counts ◽

Asymptomatic Patients ◽

Elevated Liver Enzymes

ABSTRACT Since the outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, it has rapidly spread around the world. Persons with asymptomatic disease exhibit viral shedding, resulting in transmission, which presents disease control challenges. However, the clinical characteristics of these asymptomatic individuals remain elusive. We collected samples of 25 asymptomatic and 27 symptomatic COVID-19 patients. Viral titers of throat swabs were determined by quantitative reverse transcription-PCR (qRT-PCR). COVID-19 IgG and IgM were examined. Complete blood counts were determined, and serum biochemistry panels were performed. Cytokines, including gamma interferon (IFN-γ), tumor necrosis factor alpha (TNF-α), interleukin 2 (IL-2), IL-4, IL-6, and IL-10 were evaluated. T cell, B cell, and NK cell counts were measured using flow cytometry. Although similar viral loads were detected, asymptomatic patients had significantly faster virus turnover than symptomatic patients. Additionally, asymptomatic patients had higher counts of lymphocytes, T cells, B cells, and NK cells. While liver damage was observed in symptomatic patients, as indicated by elevated liver enzymes and decreased liver-synthesized proteins in the blood, asymptomatic patients showed normal liver measurements. Lactate dehydrogenase, a COVID-19 risk factor, was significantly lower in asymptomatic patients. These results suggest that asymptomatic COVID-19 patients had normal clinical indicators and faster viral clearance than symptomatic patients. Lymphocytes may play a role in their asymptomatic phenotype. Since asymptomatic patients may be a greater risk of virus transmission than symptomatic patients, public health interventions and a broader range of testing may be necessary for the control of COVID-19. IMPORTANCE Asymptomatic transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a potential problem for pandemic control through public health strategies. Our results demonstrate that asymptomatic COVID-19 patients have better outcomes than symptomatic patients. This may have been due to more active cellular immune responses and normal liver function. Since asymptomatic patients have no clinical symptoms which can easily prevent timely diagnosis and treatment, they may cause a greater risk of virus transmission than symptomatic patients, which poses a major challenge to infection control. Evidence suggests that nonpharmaceutical public health interventions, like social distancing and face mask ordinances, play important roles in the control of COVID-19. Looking forward, it may be necessary to proceed cautiously while reopening businesses in areas of epidemicity to prevent potential waves of COVID-19 in the future.

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