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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): e25695, 2021 04 28.
Article in English | MEDLINE | ID: covidwho-2141304

ABSTRACT

BACKGROUND: The COVID-19 pandemic has severely impacted Europe, resulting in a high caseload and deaths that varied by country. The second wave of the COVID-19 pandemic has breached the borders of Europe. Public health surveillance is necessary to inform policy and guide leaders. OBJECTIVE: This study aimed to provide advanced surveillance metrics for COVID-19 transmission that account for weekly shifts in the pandemic, speed, acceleration, jerk, and persistence, to better understand countries at risk for explosive growth and those that are managing the pandemic effectively. METHODS: We performed a longitudinal trend analysis and extracted 62 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in Europe 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: New COVID-19 cases slightly decreased from 158,741 (week 1, January 4-10, 2021) to 152,064 (week 2, January 11-17, 2021), and cumulative cases increased from 22,507,271 (week 1) to 23,890,761 (week 2), with a weekly increase of 1,383,490 between January 10 and January 17. France, Germany, Italy, Spain, and the United Kingdom had the largest 7-day moving averages for new cases during week 1. During week 2, the 7-day moving average for France and Spain increased. From week 1 to week 2, the speed decreased (37.72 to 33.02 per 100,000), acceleration decreased (0.39 to -0.16 per 100,000), and jerk increased (-1.30 to 1.37 per 100,000). CONCLUSIONS: The United Kingdom, Spain, and Portugal, in particular, are at risk for a rapid expansion in COVID-19 transmission. An examination of the European region suggests that there was a decrease in the COVID-19 caseload between January 4 and January 17, 2021. Unfortunately, the rates of jerk, which were negative for Europe at the beginning of the month, reversed course and became positive, despite decreases in speed and acceleration. Finally, the 7-day persistence rate was higher during week 2 than during week 1. These measures indicate that the second wave of the pandemic may be subsiding, but some countries remain at risk for new outbreaks and increased transmission in the absence of rapid policy responses.


Subject(s)
COVID-19/epidemiology , Public Health Surveillance , Europe/epidemiology , Humans , Longitudinal Studies
3.
J Med Internet Res ; 22(12): e24286, 2020 12 03.
Article in English | MEDLINE | ID: covidwho-978988

ABSTRACT

BACKGROUND: The emergence of SARS-CoV-2, the virus that causes COVID-19, has led to a global pandemic. The United States has been severely affected, accounting for the most COVID-19 cases and deaths worldwide. Without a coordinated national public health plan informed by surveillance with actionable metrics, the United States has been ineffective at preventing and mitigating the escalating COVID-19 pandemic. Existing surveillance has incomplete ascertainment and is limited by the use of standard surveillance metrics. Although many COVID-19 data sources track infection rates, informing prevention requires capturing the relevant dynamics of the pandemic. OBJECTIVE: The aim of this study is to develop dynamic metrics for public health surveillance that can inform worldwide COVID-19 prevention efforts. Advanced surveillance techniques are essential to inform public health decision making and to identify where and when corrective action is required to prevent outbreaks. METHODS: Using a longitudinal trend analysis study design, we extracted COVID-19 data from global public health registries. We used an empirical difference equation to measure daily case numbers for our use case in 50 US states and the District of Colombia 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: Examination of the United States and state data demonstrated that most US states are experiencing outbreaks as measured by these new metrics of speed, acceleration, jerk, and persistence. Larger US states have high COVID-19 caseloads as a function of population size, density, and deficits in adherence to public health guidelines early in the epidemic, and other states have alarming rates of speed, acceleration, jerk, and 7-day persistence in novel infections. North and South Dakota have had the highest rates of COVID-19 transmission combined with positive acceleration, jerk, and 7-day persistence. Wisconsin and Illinois also have alarming indicators and already lead the nation in daily new COVID-19 infections. As the United States enters its third wave of COVID-19, all 50 states and the District of Colombia have positive rates of speed between 7.58 (Hawaii) and 175.01 (North Dakota), and persistence, ranging from 4.44 (Vermont) to 195.35 (North Dakota) new infections per 100,000 people. CONCLUSIONS: Standard surveillance techniques such as daily and cumulative infections and deaths are helpful but only provide a static view of what has already occurred in the pandemic and are less helpful in prevention. Public health policy that is informed by dynamic surveillance can shift the country from reacting to COVID-19 transmissions to being proactive and taking corrective action when indicators of speed, acceleration, jerk, and persistence remain positive week over week. Implicit within our dynamic surveillance is an early warning system that indicates when there is problematic growth in COVID-19 transmissions as well as signals when growth will become explosive without action. A public health approach that focuses on prevention can prevent major outbreaks in addition to endorsing effective public health policies. Moreover, subnational analyses on the dynamics of the pandemic allow us to zero in on where transmissions are increasing, meaning corrective action can be applied with precision in problematic areas. Dynamic public health surveillance can inform specific geographies where quarantines are necessary while preserving the economy in other US areas.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Public Health Surveillance , COVID-19/epidemiology , COVID-19/mortality , Humans , Longitudinal Studies , Pandemics/prevention & control , Pandemics/statistics & numerical data , Public Health , Registries , SARS-CoV-2 , United States/epidemiology
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