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1.
JMIR Public Health Surveill ; 7(6): e24251, 2021 06 17.
Article in English | MEDLINE | ID: covidwho-2197876

ABSTRACT

BACKGROUND: COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia. OBJECTIVE: This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks. METHODS: We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in South Asia as a function of the prior number of cases, the level of testing, and weekly shifts in variables with a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Traditional surveillance metrics indicate that South Asian countries have an alarming outbreak, with India leading the region with 310,310 new daily cases in accordance with the 7-day moving average. Enhanced surveillance indicates that while Pakistan and Bangladesh still have a high daily number of new COVID-19 cases (n=4819 and n=3878, respectively), their speed of new infections declined from April 12-25, 2021, from 2.28 to 2.18 and 3.15 to 2.35 daily new infections per 100,000 population, respectively, which suggests that their outbreaks are decreasing and that these countries are headed in the right direction. In contrast, India's speed of new infections per 100,000 population increased by 52% during the same period from 14.79 to 22.49 new cases per day per 100,000 population, which constitutes an increased outbreak. CONCLUSIONS: Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control/statistics & numerical data , Disease Outbreaks/statistics & numerical data , Health Policy , Public Health/statistics & numerical data , Adult , Aged , Aged, 80 and over , Asia/epidemiology , COVID-19/prevention & control , Communicable Disease Control/legislation & jurisprudence , Female , Humans , Longitudinal Studies , Male , Middle Aged , Public Health Surveillance , SARS-CoV-2
2.
JMIR Public Health Surveill ; 7(4): e25728, 2021 04 27.
Article in English | MEDLINE | ID: covidwho-2141306

ABSTRACT

BACKGROUND: The COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic. OBJECTIVE: This study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics. METHODS: Through a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. COVID-19 transmission rates were tracked for the LAC between September 30 and October 6, 2020, and between October 7 and 13, 2020. RESULTS: The LAC saw a reduction in the speed, acceleration, and jerk for the week of October 13, 2020, compared to the week of October 6, 2020, accompanied by reductions in new cases and the 7-day moving average. For the week of October 6, 2020, Belize reported the highest acceleration and jerk, at 1.7 and 1.8, respectively, which is particularly concerning, given its high mortality rate. The Bahamas also had a high acceleration at 1.5. In total, 11 countries had a positive acceleration during the week of October 6, 2020, whereas only 6 countries had a positive acceleration for the week of October 13, 2020. The TAC displayed an overall positive trend, with a speed of 10.40, acceleration of 0.27, and jerk of -0.31, all of which decreased in the subsequent week to 9.04, -0.81, and -0.03, respectively. CONCLUSIONS: Metrics such as new cases, cumulative cases, deaths, and 7-day moving averages provide a static view of the pandemic but fail to identify where and the speed at which SARS-CoV-2 infects new individuals, the rate of acceleration or deceleration of the pandemic, and weekly comparison of the rate of acceleration of the pandemic indicate impending explosive growth or control of the pandemic. Enhanced surveillance will inform policymakers and leaders in the LAC about COVID-19 outbreaks.


Subject(s)
COVID-19/epidemiology , Public Health Surveillance , Caribbean Region/epidemiology , Humans , Latin America/epidemiology , Longitudinal Studies
3.
Journal of Medical Internet Research Vol 23(2), 2021, ArtID e25454 ; 23(2), 2021.
Article in English | APA PsycInfo | ID: covidwho-1451697

ABSTRACT

Background: Government responses to managing the COVID-19 pandemic may have impacted the way individuals were able to engage in physical activity. Digital platforms are a promising way to support physical activity levels and may have provided an alternative for people to maintain their activity while at home. Objective: This study aimed to examine associations between the use of digital platforms and adherence to the physical activity guidelines among Australian adults and adolescents during the COVID-19 stay-at-home restrictions in April and May 2020. Methods: A national online survey was distributed in May 2020. Participants included 1188 adults (mean age 37.4 years, SD 15.1;980/1188, 82.5% female) and 963 adolescents (mean age 16.2 years, SD 1.2;685/963, 71.1% female). Participants reported demographic characteristics, use of digital platforms for physical activity over the previous month, and adherence to moderate- to vigorous-intensity physical activity (MVPA) and muscle-strengthening exercise (MSE) guidelines. Multilevel logistic regression models examined differences in guideline adherence between those who used digital platforms (ie, users) to support their physical activity compared to those who did not (ie, nonusers). Results: Digital platforms include streaming services for exercise (eg, YouTube, Instagram, and Facebook);subscriber fitness programs, via an app or online (eg, Centr and MyFitnessPal);facilitated online live or recorded classes, via platforms such as Zoom (eg, dance, sport training, and fitness class);sport- or activity-specific apps designed by sporting organizations for participants to keep up their skills (eg, TeamBuildr);active electronic games (eg, Xbox Kinect);and/or online or digital training or racing platforms (eg, Zwift, FullGaz, and Rouvy). Overall, 39.5% (469/1188) of adults and 26.5% (255/963) of adolescents reported using digital platforms for physical activity. Among adults, MVPA (odds ratio [OR] 2.0, 95% CI 1.5-2.7), MSE (OR 3.3, 95% CI 2.5-4.5), and combined (OR 2.7, 95% CI 2.0-3.8) guideline adherence were higher among digital platform users relative to nonusers. Adolescents' MVPA (OR 2.4, 95% CI 1.3-4.3), MSE (OR 3.1, 95% CI 2.1-4.4), and combined (OR 4.3, 95% CI 2.1-9.0) guideline adherence were also higher among users of digital platforms relative to nonusers. Conclusions: Digital platform users were more likely than nonusers to meet MVPA and MSE guidelines during the COVID-19 stay-at-home restrictions in April and May 2020. Digital platforms may play a critical role in helping to support physical activity engagement when access to facilities or opportunities for physical activity outside the home are restricted. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

4.
JMIR Public Health Surveill ; 7(5): e25753, 2021 05 10.
Article in English | MEDLINE | ID: covidwho-1183763

ABSTRACT

BACKGROUND: The COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur. OBJECTIVE: The goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk, and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have controlled outbreaks successfully. METHODS: Using a longitudinal trend analysis study design, we extracted 62 days of COVID-19 data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: We compare the week of February 7-13, 2021, with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID-19 transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5 daily new cases per 100,000 population for the week of February 7-13 to speeds of 6.9 and 9.3 for the week of February 14-20, respectively. Nunavut experienced a significant increase in speed during this time, from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population. CONCLUSIONS: Canada excelled at COVID-19 control early on in the pandemic, especially during the first COVID-19 shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak, which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth, which informs proactive health policy.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Public Health Surveillance/methods , Canada/epidemiology , Humans , Longitudinal Studies
5.
J Med Internet Res ; 23(2): e25799, 2021 02 03.
Article in English | MEDLINE | ID: covidwho-1069699

ABSTRACT

BACKGROUND: SARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19. OBJECTIVE: The goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully. METHODS: Using a longitudinal trend analysis study design, we extracted 60 days of COVID-19-related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: COVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight. CONCLUSIONS: The rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Administrative Personnel , Armenia/epidemiology , Asia, Central/epidemiology , Azerbaijan/epidemiology , Benchmarking , Cyprus/epidemiology , Denmark/epidemiology , Food Insecurity , Georgia (Republic)/epidemiology , Gibraltar/epidemiology , Humans , Kosovo/epidemiology , Longitudinal Studies , Pandemics/prevention & control , Public Health , Public Health Surveillance/methods , Registries , Republic of North Macedonia/epidemiology , Russia/epidemiology , SARS-CoV-2 , Turkey/epidemiology , Water Insecurity
6.
J Med Internet Res ; 23(2): e25454, 2021 02 01.
Article in English | MEDLINE | ID: covidwho-1058365

ABSTRACT

BACKGROUND: The COVID-19 pandemic has had a profound global impact on governments, health care systems, economies, and populations around the world. Within the East Asia and Pacific region, some countries have mitigated the spread of the novel coronavirus effectively and largely avoided severe negative consequences, while others still struggle with containment. As the second wave reaches East Asia and the Pacific, it becomes more evident that additional SARS-CoV-2 surveillance is needed to track recent shifts, rates of increase, and persistence associated with the pandemic. OBJECTIVE: The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk, persistence, and weekly shifts, to better understand country risk for explosive growth and those countries who are managing the pandemic successfully. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. We provide novel indicators to measure disease transmission. METHODS: Using a longitudinal trend analysis study design, we extracted 330 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in East Asia and the Pacific as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: The standard surveillance metrics for Indonesia, the Philippines, and Myanmar were concerning as they had the largest new caseloads at 4301, 2588, and 1387, respectively. When looking at the acceleration of new COVID-19 infections, we found that French Polynesia, Malaysia, and the Philippines had rates at 3.17, 0.22, and 0.06 per 100,000. These three countries also ranked highest in terms of jerk at 15.45, 0.10, and 0.04, respectively. CONCLUSIONS: Two of the most populous countries in East Asia and the Pacific, Indonesia and the Philippines, have alarming surveillance metrics. These two countries rank highest in new infections in the region. The highest rates of speed, acceleration, and positive upwards jerk belong to French Polynesia, Malaysia, and the Philippines, and may result in explosive growth. While all countries in East Asia and the Pacific need to be cautious about reopening their countries since outbreaks are likely to occur in the second wave of COVID-19, the country of greatest concern is the Philippines. Based on standard and enhanced surveillance, the Philippines has not gained control of the COVID-19 epidemic, which is particularly troubling because the country ranks 4th in population in the region. Without extreme and rigid social distancing, quarantines, hygiene, and masking to reverse trends, the Philippines will remain on the global top 5 list of worst COVID-19 outbreaks resulting in high morbidity and mortality. The second wave will only exacerbate existing conditions and increase COVID-19 transmissions.


Subject(s)
COVID-19/epidemiology , Asia, Southeastern/epidemiology , Australasia/epidemiology , COVID-19/transmission , Asia, Eastern/epidemiology , Health Policy , Humans , Indonesia/epidemiology , Longitudinal Studies , Malaysia/epidemiology , Pandemics , Philippines/epidemiology , Polynesia/epidemiology , Public Health , Public Health Surveillance , Registries , SARS-CoV-2
7.
J Med Internet Res ; 23(1): e25830, 2021 01 15.
Article in English | MEDLINE | ID: covidwho-968790

ABSTRACT

BACKGROUND: The COVID-19 pandemic has disrupted the lives of millions and forced countries to devise public health policies to reduce the pace of transmission. In the Middle East and North Africa (MENA), falling oil prices, disparities in wealth and public health infrastructure, and large refugee populations have significantly increased the disease burden of COVID-19. In light of these exacerbating factors, public health surveillance is particularly necessary to help leaders understand and implement effective disease control policies to reduce SARS-CoV-2 persistence and transmission. OBJECTIVE: The goal of this study is to provide advanced surveillance metrics, in combination with traditional surveillance, for COVID-19 transmission that account for weekly shifts in the pandemic speed, acceleration, jerk, and persistence to better understand a country's risk for explosive growth and to better inform those who are managing the pandemic. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. METHODS: Using a longitudinal trend analysis study design, we extracted 30 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in MENA as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: The regression Wald statistic was significant (χ25=859.5, P<.001). The Sargan test was not significant, failing to reject the validity of overidentifying restrictions (χ2294=16, P=.99). Countries with the highest cumulative caseload of the novel coronavirus include Iran, Iraq, Saudi Arabia, and Israel with 530,380, 426,634, 342,202, and 303,109 cases, respectively. Many of the smaller countries in MENA have higher infection rates than those countries with the highest caseloads. Oman has 33.3 new infections per 100,000 population while Bahrain has 12.1, Libya has 14, and Lebanon has 14.6 per 100,000 people. In order of largest to smallest number of cumulative deaths since January 2020, Iran, Iraq, Egypt, and Saudi Arabia have 30,375, 10,254, 6120, and 5185, respectively. Israel, Bahrain, Lebanon, and Oman had the highest rates of COVID-19 persistence, which is the number of new infections statistically related to new infections in the prior week. Bahrain had positive speed, acceleration, and jerk, signaling the potential for explosive growth. CONCLUSIONS: Static and dynamic public health surveillance metrics provide a more complete picture of pandemic progression across countries in MENA. Static measures capture data at a given point in time such as infection rates and death rates. By including speed, acceleration, jerk, and 7-day persistence, public health officials may design policies with an eye to the future. Iran, Iraq, Saudi Arabia, and Israel all demonstrated the highest rate of infections, acceleration, jerk, and 7-day persistence, prompting public health leaders to increase prevention efforts.


Subject(s)
COVID-19/epidemiology , Africa, Northern/epidemiology , Humans , Longitudinal Studies , Middle East/epidemiology , Pandemics , Public Health Surveillance/methods , SARS-CoV-2/isolation & purification
8.
J Med Internet Res ; 22(11): e24248, 2020 11 19.
Article in English | MEDLINE | ID: covidwho-934414

ABSTRACT

BACKGROUND: Since the novel coronavirus emerged in late 2019, the scientific and public health community around the world have sought to better understand, surveil, treat, and prevent the disease, COVID-19. In sub-Saharan Africa (SSA), many countries responded aggressively and decisively with lockdown measures and border closures. Such actions may have helped prevent large outbreaks throughout much of the region, though there is substantial variation in caseloads and mortality between nations. Additionally, the health system infrastructure remains a concern throughout much of SSA, and the lockdown measures threaten to increase poverty and food insecurity for the subcontinent's poorest residents. The lack of sufficient testing, asymptomatic infections, and poor reporting practices in many countries limit our understanding of the virus's impact, creating a need for better and more accurate surveillance metrics that account for underreporting and data contamination. OBJECTIVE: The goal of this study is to improve infectious disease surveillance by complementing standardized metrics with new and decomposable surveillance metrics of COVID-19 that overcome data limitations and contamination inherent in public health surveillance systems. In addition to prevalence of observed daily and cumulative testing, testing positivity rates, morbidity, and mortality, we derived COVID-19 transmission in terms of speed, acceleration or deceleration, change in acceleration or deceleration (jerk), and 7-day transmission rate persistence, which explains where and how rapidly COVID-19 is transmitting and quantifies shifts in the rate of acceleration or deceleration to inform policies to mitigate and prevent COVID-19 and food insecurity in SSA. METHODS: We extracted 60 days of COVID-19 data from public health registries and employed an empirical difference equation to measure daily case numbers in 47 sub-Saharan countries as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Kenya, Ghana, Nigeria, Ethiopia, and South Africa have the most observed cases of COVID-19, and the Seychelles, Eritrea, Mauritius, Comoros, and Burundi have the fewest. In contrast, the speed, acceleration, jerk, and 7-day persistence indicate rates of COVID-19 transmissions differ from observed cases. In September 2020, Cape Verde, Namibia, Eswatini, and South Africa had the highest speed of COVID-19 transmissions at 13.1, 7.1, 3.6, and 3 infections per 100,0000, respectively; Zimbabwe had an acceleration rate of transmission, while Zambia had the largest rate of deceleration this week compared to last week, referred to as a jerk. Finally, the 7-day persistence rate indicates the number of cases on September 15, 2020, which are a function of new infections from September 8, 2020, decreased in South Africa from 216.7 to 173.2 and Ethiopia from 136.7 to 106.3 per 100,000. The statistical approach was validated based on the regression results; they determined recent changes in the pattern of infection, and during the weeks of September 1-8 and September 9-15, there were substantial country differences in the evolution of the SSA pandemic. This change represents a decrease in the transmission model R value for that week and is consistent with a de-escalation in the pandemic for the sub-Saharan African continent in general. CONCLUSIONS: Standard surveillance metrics such as daily observed new COVID-19 cases or deaths are necessary but insufficient to mitigate and prevent COVID-19 transmission. Public health leaders also need to know where COVID-19 transmission rates are accelerating or decelerating, whether those rates increase or decrease over short time frames because the pandemic can quickly escalate, and how many cases today are a function of new infections 7 days ago. Even though SSA is home to some of the poorest countries in the world, development and population size are not necessarily predictive of COVID-19 transmission, meaning higher income countries like the United States can learn from African countries on how best to implement mitigation and prevention efforts. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/21955.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Health Policy , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Public Health Surveillance , Africa South of the Sahara/epidemiology , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/virology , Female , Humans , Male , Models, Biological , Pandemics , Pneumonia, Viral/virology , Registries , SARS-CoV-2
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