SARS-CoV-2 Surveillance in the Middle East and North Africa: Longitudinal Trend Analysis.

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.

SARS-CoV-2 Wave Two Surveillance in East Asia and the Pacific: Longitudinal Trend Analysis.

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.

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

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.

A SARS-CoV-2 Surveillance System in Sub-Saharan Africa: Modeling Study for Persistence and Transmission to Inform Policy.

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.

Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study.

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.

Perspectives of the cohort of health professionals in the WiSDOM study on the learning environment, transformation, and social accountability at a South African University.

BACKGROUND: The dearth of empirical research on transformative health professions education informed this study to examine the factors that influence the perspectives of the cohort of health professionals in the WiSDOM study on the learning environment, transformation, and social accountability at a South African university. METHODS: WiSDOM, a prospective longitudinal cohort study, consists of eight health professional groups: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists. At study inception in 2017, participants completed a self-administered questionnaire that included four domains of selection criteria (6 items); the learning environment (5 items); redress and transformation (8 items); and social accountability (5 items). In the analysis, we, rescaled the original Likert scoring of 1 (strongly disagree) to 7 (strongly agree) to a new scale ranging from 0-10. We calculated the mean scores for each item and across items for the four domains, with low scores (0.00-1.99) classified as poor and high scores (8.00-10.00) as excellent. We used multiple linear regression analysis to compare the mean scores, while adjusting for different socio-demographiccharacteristics. RESULTS: The mean age of the 501 eligible participants was 24.1 years; the majority female (72.9%), 45.3% self-identified as Black African; and 12.2% were born in a rural area. The domains of selection criteria and redress and transformation obtained mean scores of 5.4 and 5.3 out of 10 respectively, while social accountability and the learning environment obtained mean scores of 6.1 and 7.4 out of 10 respectively. Self-identified race influenced the overall mean scores of selection criteria, redress and transformation, and social accountability (p < 0.001). Rural birth influenced the perceptions on selection criteria, redress and transformation (p < 0.01). CONCLUSION: The results suggest the need to create inclusive learning environments that foreground redress, transformation, and social accountability, while advancing the discourse on decolonised health sciences education.

Rehabilitation Capacity in South Africa-A Situational Analysis.

Rehabilitation in South Africa (SA) operates independently of major health services and reforms, despite the increasing rehabilitation need. With the introduction of National Health Insurance (NHI), SA is facing another major health reform. Evidence is needed on the current SA rehabilitation situation, regarding shortcomings, opportunities, and priority strategic strengthening actions. We aimed to describe the current rehabilitation capacity in the SA public health sector, which serves the majority and most vulnerable South Africans. A cross-sectional survey was conducted in five provinces, using the World Health Organisation's Template for Rehabilitation Information Collection (TRIC). Participants were purposively selected for their insights and experiences of rehabilitation in specific government departments, health sectors, organisations, and/or services. TRIC responses were analysed descriptively. Participants explained how timely and effective rehabilitation produced long-term health, social, and economic benefits. Positive initiatives were reported for rehabilitation data collection, service design, and innovation. Challenges included inadequacies in human resources, the integration of rehabilitation at primary care, guidelines, and specialised long-term care facilities. The continuity of care across levels of care was sub-optimal due to inefficient referral systems. Promoting and improving rehabilitation nationally requires concerted, innovative, collaborative, and integrated efforts from multiple stakeholders within, and outside, the health system.

Has Omicron Changed the Evolution of the Pandemic?

BACKGROUND: Variants of the SARS-CoV-2 virus carry differential risks to public health. The Omicron (B.1.1.529) variant, first identified in Botswana on November 11, 2021, has spread globally faster than any previous variant of concern. Understanding the transmissibility of Omicron is vital in the development of public health policy. OBJECTIVE: The aim of this study is to compare SARS-CoV-2 outbreaks driven by Omicron to those driven by prior variants of concern in terms of both the speed and magnitude of an outbreak. METHODS: We analyzed trends in outbreaks by variant of concern with validated surveillance metrics in several southern African countries. The region offers an ideal setting for a natural experiment given that most outbreaks thus far have been driven primarily by a single variant at a time. With a daily longitudinal data set of new infections, total vaccinations, and cumulative infections in countries in sub-Saharan Africa, we estimated how the emergence of Omicron has altered the trajectory of SARS-CoV-2 outbreaks. We used the Arellano-Bond method to estimate regression coefficients from a dynamic panel model, in which new infections are a function of infections yesterday and last week. We controlled for vaccinations and prior infections in the population. To test whether Omicron has changed the average trajectory of a SARS-CoV-2 outbreak, we included an interaction between an indicator variable for the emergence of Omicron and lagged infections. RESULTS: The observed Omicron outbreaks in this study reach the outbreak threshold within 5-10 days after first detection, whereas other variants of concern have taken at least 14 days and up to as many as 35 days. The Omicron outbreaks also reach peak rates of new cases that are roughly 1.5-2 times those of prior variants of concern. Dynamic panel regression estimates confirm Omicron has created a statistically significant shift in viral spread. CONCLUSIONS: The transmissibility of Omicron is markedly higher than prior variants of concern. At the population level, the Omicron outbreaks occurred more quickly and with larger magnitude, despite substantial increases in vaccinations and prior infections, which should have otherwise reduced susceptibility to new infections. Unless public health policies are substantially altered, Omicron outbreaks in other countries are likely to occur with little warning.

Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates.

BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta. OBJECTIVE: The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred. METHODS: We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate. RESULTS: Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak. CONCLUSIONS: These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts.

Policy exclusion or confusion? Perspectives on universal health coverage for migrants and refugees in South Africa.

Notwithstanding the promise of the inclusivity of universal health coverage (UHC), the integration of migrants and refugees into host countries' health systems remains elusive and contested. In South Africa, there is insufficient scholarly attention on UHC, migrants and refugees, given the country's strategic importance in Africa and the envisaged implementation of the National Health Insurance (NHI) system. In this paper, a social exclusion conceptual framework is used to explore whether South African legislation, health policies and perspectives or actions of health policy actors facilitate UHC for migrants and refugees or exacerbate their exclusion. We combined a review of legislation and policies since 1994, with semi-structured interviews with 18 key informants from government, academia, civil society organizations and a United Nations organization. We used thematic analysis to identify themes and sub-themes from the qualitative data. The South African Constitution and the National Health Act facilitate UHC, while the Immigration Act and the 2019 NHI Bill make the legal status of migrants the most significant determinant of healthcare access. This legislative disjuncture is exacerbated by variations in content, interpretation and/or implementation of policies at the provincial level. Resource constraints in the public health sector contribute to the perceived dysfunctionality of the public healthcare system, which affects the financial classification, quality of care and access for all public sector patients. However, migrants and refugees bear the brunt of the reported dysfunctionality, in addition to experiences of medical xenophobia. These issues need to be addressed to ensure that South Africa's quest for UHC expressed through the NHI system is realized.

Methodological considerations in establishing and maintaining longitudinal health workforce studies: Lessons learned from the WiSDOM cohort in South Africa.

BACKGROUND: Health workforce cohort studies are uncommon in low-and middle-income countries (LMICs), especially those in sub-Saharan Africa. OBJECTIVE: Describe the methodology and lessons learned from establishing and maintaining the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) health professional cohort study in South Africa. METHODS: WiSDOM is a prospective longitudinal cohort study that commenced in 2017. The cohort focuses on the eight professional groups of clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists and physiotherapists. Annual, electronic follow-up surveys have been conducted in 2018, 2019 and 2020 with informed consent. Key steps in establishing the WiSDOM cohort include consultation, communication and marketing, stakeholder feedback, resources and infrastructure. Retention strategies consist of an electronic database, detailed cohort contact information, cohort engagement, communication and feedback, short survey tools, and appropriate incentives. RESULTS: We obtained an overall response rate of 89.5% at baseline in 2017, 79.6% in 2018, 68.3% in 2019 and 72.8% in 2020. The largest decline in response rates is for medical doctors: 66.0% response rate in 2018, 53.2% in 2019 and 58.2% in 2020. However, for each of the three follow-up surveys, we have obtained response rates in excess of 80% for clinical associates, dentists, nurses, oral hygienists, pharmacists and physiotherapists. Since baseline, the outright refusals have remained very low at 4.7%. The multiple logistic regression analysis showed that self-identified race was the only significant socio-demographic difference between medical doctor respondents and non-respondents. Black African doctors and Indian doctors were 2.0 and 2.6 times more likely respectively to respond than White doctors (p < 0.05). CONCLUSION: Other LMICs can learn from WiSDOM's lessons of establishing and maintaining a health professional cohort that aims to generate new knowledge for health system transformation.

SARS-CoV-2 Surveillance System in Canada: Longitudinal Trend Analysis.

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.

Surveillance of the Second Wave of COVID-19 in Europe: Longitudinal Trend Analyses.

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.

Latin America and the Caribbean SARS-CoV-2 Surveillance: Longitudinal Trend Analysis.

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.

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

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.

Migrants' perceptions of health system responsiveness and satisfaction with health workers in a South African Province.

Background: There is global emphasis on quality universal health coverage (UHC) that is responsive to the needs of vulnerable communities, such as migrants. Objective: Examine the perceptions of migrants on health system responsiveness (HSR) and their satisfaction with health workers in public health facilities of a South African Province. Method: We conducted a cross-sectional study in 13 public health facilities. Following informed consent, we used a semi-structured questionnaire to collect sociodemographic information, patient perceptions of HSR and their satisfaction with health workers. Two open-ended questions gave patients the opportunity to comment on the health facility visit. We applied descriptive and multivariate analyses to our data, and thematic analysis to the qualitative responses. Results: A total of 251 migrant patients participated in the study, giving a response rate of 80.7%. The majority of patients were female (81.1%), and the mean age was 31.4 years. 30.0% of patients reported that they waited too long; 94.3% that the consulting nurse or doctor listened to them; and 89.4% that they received information about their condition. However, 81.7% said they did not know the name of the consulting nurse or doctor. The mean scores on patients' satisfaction with health workers ranged from 7.0 (95% CI 6.42-7.63) for clerks, 7.7 (95% CI 7.4-8.0) for security guards, 7.4 (95% CI 7.1-7.6) for nurses and 8.3 (95% CI 7.93-8.63) for doctors. The predictors of patient satisfaction with nurses were being given information about their condition; polite treatment, time spent in facility, whether they received prescribed medicines; and stating that they would refer the health facility to family/friends. Four overlapping themes emerged: health workers' attitudes; time waited at the health facility, communication difficulties; and sub-optimal procedures in the health facility. Conclusion: UHC policies should incorporate migrant patients' perceptions of HSR and the determinants of their satisfaction with health workers.

Social exclusion and the perspectives of health care providers on migrants in Gauteng public health facilities, South Africa.

BACKGROUND: Universal health coverage (UHC) for all people, regardless of citizenship, is a global priority. Health care providers are central to the achievement of UHC, and their attitudes and behaviour could either advance or impede UHC for migrants. Using a social exclusion conceptual framework, this study examined the perspectives of health care providers on delivering health services to migrants in public health facilities in Gauteng Province, South Africa. METHODS: We used stratified, random sampling to select 13 public health facilities. All health care providers working in ambulatory care were invited to complete a self-administered questionnaire. In addition to socio-demographic information, the questionnaire asked health care providers if they had witnessed discrimination against migrants at work, and measured their perspectives on social exclusionary views and practices. Multiple regression analysis was used to identify predictors of more exclusionary perspectives for each item. RESULTS: 277 of 308 health care providers participated in the study-a response rate of 90%. The participants were predominantly female (77.6%) and nurses (51.9%), and had worked for an average of 6.8 years in their facilities. 19.2% of health care providers reported that they had witnessed discrimination against migrants, while 20.0% reported differential treatment of migrant patients. Exclusionary perspectives varied across the different items, and for different provider groups. Enrolled nurses and nursing assistants were significantly more exclusionary on a number of items, while the opposite was found for providers born outside South Africa. For some questions, female providers held more exclusionary perspectives and this was also the case for providers from higher levels of care. CONCLUSION: Health care providers are critical to inclusive UHC. Social exclusionary views or practices must be addressed through enabling health policies; training in culture-sensitivity, ethics and human rights; and advocacy to ensure that health care providers uphold their professional obligations to all patients.

Socio-economic characteristics and career intentions of the WiSDOM health professional cohort in South Africa.

BACKGROUND: The human resources for health (HRH) crisis and dearth of research on the health labour market in South Africa informed the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) cohort study. The study aims to generate new knowledge on the career choices and job location decisions of health professionals in South Africa. METHODS: WiSDOM is a prospective longitudinal cohort study. During 2017, the first cohort for each of eight professional groups was established: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists and physiotherapists. These cohorts will be followed up for 15 years. For the baseline data collection, each final year health professional student completed an electronic self-administered questionnaire (SAQ), after providing informed consent. The SAQ included information on: demographic characteristics; financing of training; reasons for choosing their profession; and their career intentions. We used STATA® 14 to analyse the data. RESULTS: We obtained an 89.5% response rate and 511 final year health professional students completed the baseline survey. The mean age of all participants was 24.1 years; 13.1% were born in a rural area; 11.9% and 8.0% completed their primary and secondary schooling in a rural area respectively. The health professional students came from relatively privileged backgrounds: 45.0% had attended a private school, the majority of their fathers (77.1%) had completed tertiary education, and 69.1% of their mothers had completed tertiary education. Students with higher socio-economic status (SES Quintiles 3-5) made up a larger proportion of the occupational therapists (77.8%), physiotherapists (71.7%), doctors (66.7%), and dentists (64.7%). In contrast, individuals from SES Quintiles 1 and 2 were over-represented among the clinical associates (75.0%), oral hygienists (71.4%), nurses (61.9%), and pharmacists (56.9%). Almost one quarter (24.9%) of cohort members indicated that they had partly financed their studies through loans. Although 86.3% of all cohort members indicated that they plan to stay in their chosen profession, this ranged from 43.2% for clinical associates to 100% for dentists. CONCLUSIONS: WiSDOM has generated new knowledge on health professional graduates of a leading South African University. The results have implications for university selection criteria and national health workforce planning.

'Practice what you preach': Nurses' perspectives on the Code of Ethics and Service Pledge in five South African hospitals.

BACKGROUND: A recent focus of the global discourse on the health workforce has been on its quality, including the existence of codes of ethics. In South Africa, the importance of ethics and value systems in nursing was emphasised in the 2011 National Nursing Summit. OBJECTIVE: The study explored hospital nurses' perceptions of the International Code of Ethics for Nurses; their perceptions of the South African Nurses' Pledge of Service; and their views on contemporary ethical practice. METHODS: Following university ethics approval, the study was done at a convenience sample of five hospitals in two South African provinces. In each hospital, all day duty nurses in paediatric, maternity, adult medical, and adult surgical units were requested to complete a self-administered questionnaire. The questionnaire focused on their perceptions of the Code of Ethics and the Pledge, using a seven-point Likert scale. STATA(®) 13 and NVIVO 10 were used to analyse survey data and open-ended responses, respectively. RESULTS: The mean age of survey participants (n=69) was 39 years (SD=9.2), and the majority were female (96%). The majority agreed with a statement that they will promote the human rights of individuals (98%) and that they have a duty to meet the health and social needs of the public (96%). More nuanced responses were obtained for some questions, with 60% agreeing with a statement that too much emphasis is placed on patients' rights as opposed to nurses' rights and 32% agreeing with a statement that they would take part in strike action to improve nurses' salaries and working conditions. The dilemmas of nurses to uphold the Code of Ethics and the Pledge in face of workplace constraints or poor working conditions were revealed in nurses' responses to open-ended questions. CONCLUSION: Continuing education in ethics and addressing health system deficiencies will enhance nurses' professional development and their ethical decision-making and practice.