Surveillance Metrics of SARS-CoV-2 Transmission in Central Asia: Longitudinal Trend Analysis

Post, Lori A.; Benishay, Elana T; Moss, Charles B.; Murphy, Robert L.; Achenbach, Chad J.; Ison, Michael G.; Resnick, Danielle; Singh, Lauren Nadya; White, Janine; Chaudhury, Azraa S.; Boctor, Michael J; Welch, Sarah B; Oehmke, James F.

doi:10.2196/25799

Cited by 28 publications

(20 citation statements)

References 56 publications

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“…To that end, in addition to traditional surveillance metrics, we used dynamic panel modeling and the generalized method of moments, which correct for limitations in existing surveillance. Parallel work utilizing enhanced surveillance metrics has been completed for sub-Saharan Africa [31], the United States [32], the Middle East and North Africa [33], Central Asia [34], Europe [35], Latin America and the Caribbean [36], East Asia and the Pacific [37], Canada [38], and metropolitan regions [39].…”

Section: Objectivementioning

confidence: 99%

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The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data

Welch¹,

Kulasekere²,

Prasad³

et al. 2021

JMIR Public Health Surveill

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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.

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Section: Objectivementioning

confidence: 99%

“…We conducted similar studies based on dynamic panel data derived from other global regions [31][32][33][34][35][36][37][38][39]44,45] similar to South Asia.…”

Section: Comparison With Prior Workmentioning

confidence: 99%

The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data

Welch¹,

Kulasekere²,

Prasad³

et al. 2021

JMIR Public Health Surveill

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“…Most studies have used a static relative baseline period such as mobility trends between January until February 2020 [6,23,24]. This common approach does not account for seasonal mobility variability or changes as a result of the pandemic [25,26,27]. In contrast our baseline (rolling average) takes into consideration temporal trends that were likely changing with evolving public health policies.…”

Section: Mobility Indexmentioning

confidence: 99%

Can tracking mobility be used as a public health tool against COVID-19 following the expiration of stay-at-home mandates?

Her

Saeed²,

Tram³

et al. 2021

Preprint

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Background: Considering the emergence of SARS-CoV-2 variants and low vaccine access and uptake, minimizing human interactions remains an effective strategy to mitigate the spread of SARS-CoV-2. The aim of this study was to create a novel multidimensional mobility index to capture the complexity of human interaction and evaluate its utility as an early indicator of surges in COVID-19 cases. Methods: We used publicly available anonymous cell phone data compiled by SafeGraph, from all counties in Illinois, Ohio, Michigan and Indiana between January 1st to December 8, 2020. Six metrics of mobility were extracted for each county. Changes in mobility were defined as a time-updated 7-day rolling average. We used an unsupervised machine learning method known as functional principal component analysis (fPCA) to construct the latent mobility index (MI) using the six metrics of mobility. Associations between our MI and COVID-19 cases were estimated using a quasi-Poisson hierarchical generalized additive model adjusted for population density and the COVID-19 community vulnerability index. Results: Individual mobility metrics varied significantly by counties and by calendar time. More than 50% of the variability in the data was explained by the first principal component by each state, indicating good dimension reduction. Following the expiration of stay-at-home orders, mobility increased across all counties and this was particularly evident on weekends. While an individual metric of mobility was not associated with surges of COVID-19, our MI was independently associated with COVID-19 cases in all four states given varying time-lags. Conclusion: Following the expiration of stay-at-home orders, a single metric of mobility was not sensitive enough to capture the complexity of human interactions. Monitoring mobility can be an important public health tool, however, it should be modelled as a multidimensional construct.

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“…Mass shooting fatalities, as a particular type of gun injury event, account for <1% of all gun deaths [3] and have largely been ignored until recently [4,5]; yet, mass shooting events occur multiple times per year [6]. This information is based on insights from firearm surveillance performed by a variety of researchers, and state and federal agencies on incidence, prevalence, risk factors, injuries, deaths, and precipitating events, similar to the surveillance of infectious diseases such as COVID-19 [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. Teutch and Thacker [22] defined public health surveillance as the ongoing systematic collection, analysis, and interpretation of health data, essential to the planning, implementation, and evaluation of public health practice, closely integrated to the dissemination of these data to those who need to know and linked to prevention and control.…”

Section: Introductionmentioning

confidence: 99%

Impact of Firearm Surveillance on Gun Control Policy: Regression Discontinuity Analysis

Post¹,

Mason²,

Singh³

et al. 2021

JMIR Public Health Surveill

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Background Public mass shootings are a significant public health problem that require ongoing systematic surveillance to test and inform policies that combat gun injuries. Although there is widespread agreement that something needs to be done to stop public mass shootings, opinions on exactly which policies that entails vary, such as the prohibition of assault weapons and large-capacity magazines. Objective The aim of this study was to determine if the Federal Assault Weapons Ban (FAWB) (1994-2004) reduced the number of public mass shootings while it was in place. Methods We extracted public mass shooting surveillance data from the Violence Project that matched our inclusion criteria of 4 or more fatalities in a public space during a single event. We performed regression discontinuity analysis, taking advantage of the imposition of the FAWB, which included a prohibition on large-capacity magazines in addition to assault weapons. We estimated a regression model of the 5-year moving average number of public mass shootings per year for the period of 1966 to 2019 controlling for population growth and homicides in general, introduced regression discontinuities in the intercept and a time trend for years coincident with the federal legislation (ie, 1994-2004), and also allowed for a differential effect of the homicide rate during this period. We introduced a second set of trend and intercept discontinuities for post-FAWB years to capture the effects of termination of the policy. We used the regression results to predict what would have happened from 1995 to 2019 had there been no FAWB and also to project what would have happened from 2005 onward had it remained in place. Results The FAWB resulted in a significant decrease in public mass shootings, number of gun deaths, and number of gun injuries. We estimate that the FAWB prevented 11 public mass shootings during the decade the ban was in place. A continuation of the FAWB would have prevented 30 public mass shootings that killed 339 people and injured an additional 1139 people. Conclusions This study demonstrates the utility of public health surveillance on gun violence. Surveillance informs policy on whether a ban on assault weapons and large-capacity magazines reduces public mass shootings. As society searches for effective policies to prevent the next mass shooting, we must consider the overwhelming evidence that bans on assault weapons and/or large-capacity magazines work.

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Surveillance Metrics of SARS-CoV-2 Transmission in Central Asia: Longitudinal Trend Analysis

Cited by 28 publications

References 56 publications

The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data

The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data

Can tracking mobility be used as a public health tool against COVID-19 following the expiration of stay-at-home mandates?

Impact of Firearm Surveillance on Gun Control Policy: Regression Discontinuity Analysis

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