Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19

On March 23 2020, the UK enacted an intensive, nationwide lockdown to mitigate transmission of COVID-19. As restrictions began to ease, more localized interventions were used to target resurgences in transmission. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to targeting interventions at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. We use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. We found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance connections central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. We propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.     

Mobility restrictions and alcohol use during lockdown: “A still and dry pandemic for the many”?

Unexpected mobility disruptions during lockdown during the first wave of COVID-19 became ’tipping points’ with the potential to alter pre-pandemic routines sensitive to socialisation. This paper investigates the impact of lockdown exposure on alcohol consumption. We document two findings using information from the Google Mobility Report and longitudinal data from the Understanding Society survey (UKHLS) in the United Kingdom. First, we find a sharp reduction in both actual mobility and alcohol use (consistent with a ”still and dry pandemic for the many” hypothesis). However, we document an increase in alcohol use among heavy drinkers, implying a split behavioural response to COVID-19 mobility restrictions based on alcohol use prior to the pandemic. Second, using the predictions of the prevalence-response elasticity theory, we find that the pandemic’s reduction in social contacts is responsible for a 2.8 percentage point reduction in drinking among men.     

An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020–2021

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with R_t<1.0 as of October 31, 2021. On the forecasting front, the sub-epidemic model performs best at capturing the 30-day ahead COVID-19 trajectory compared to the Richards and generalized logistic growth model. Nevertheless, the spatial variability in the incidence rate patterns across different departments can be grouped into four distinct clusters. As the case incidence surged in July 2020, an increase in mobility patterns was also observed. On the contrary, a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued, indicating the pandemic fatigue in the country.     

Human mobility networks, travel restrictions, and the global spread of 2009 H1N1 pandemic

After the emergence of the H1N1 influenza in 2009, some countries responded with travel-related controls during the early stage of the outbreak in an attempt to contain or slow down its international spread. These controls along with self-imposed travel limitations contributed to a decline of about 40% in international air traffic to/from Mexico following the international alert. However, no containment was achieved by such restrictions and the virus was able to reach pandemic proportions in a short time. When gauging the value and efficacy of mobility and travel restrictions it is crucial to rely on epidemic models that integrate the wide range of features characterizing human mobility and the many options available to public health organizations for responding to a pandemic. Here we present a comprehensive computational and theoretical study of the role of travel restrictions in halting and delaying pandemics by using a model that explicitly integrates air travel and short-range mobility data with high-resolution demographic data across the world and that is validated by the accumulation of data from the 2009 H1N1 pandemic. We explore alternative scenarios for the 2009 H1N1 pandemic by assessing the potential impact of mobility restrictions that vary with respect to their magnitude and their position in the pandemic timeline. We provide a quantitative discussion of the delay obtained by different mobility restrictions and the likelihood of containing outbreaks of infectious diseases at their source, confirming the limited value and feasibility of international travel restrictions. These results are rationalized in the theoretical framework characterizing the invasion dynamics of the epidemics at the metapopulation level.     

Vulnerability and COVID-19 infection rates: A changing relationship during the first year of the pandemic

In the first year of the COVID-19 pandemic, Spain was one of the worst-hit countries, although not all areas and social groups were affected equally. This study focuses on Malaga, a cosmopolitan tourist destination located on the southern Mediterranean coast that has the sixth largest population in Spain. Specifically, it examines the relationship between multidimensional vulnerability and COVID-19 infection rates across the city’s census tracts for the period February 2020 to February 2021. The analysis uses high frequency (daily) data on the accumulated incidence of the disease at 14 days and shows that COVID-19 did not spread symmetrically across the census tracts of Malaga but had a greater impact on the most vulnerable neighbourhoods. However, the pattern of this relationship was not uniform in the period examined, with specific contextual factors driving the higher infection rates across time. Our findings show that pandemic containment regulations cannot overlook vulnerability considerations and universal restrictions to reduce the spread of disease should be supplemented by targeted regulations for specific areas.     

Healthcare utilization and maternal and child mortality during the COVID-19 pandemic in 18 low- and middle-income countries: An interrupted time-series analysis with mathematical modeling of administrative data

BackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic has had wide-reaching direct and indirect impacts on population health. In low- and middle-income countries, these impacts can halt progress toward reducing maternal and child mortality. This study estimates changes in health services utilization during the pandemic and the associated consequences for maternal, neonatal, and child mortality.Methods and findingsData on service utilization from January 2018 to June 2021 were extracted from health management information systems of 18 low- and lower-middle-income countries (Afghanistan, Bangladesh, Cameroon, Democratic Republic of the Congo (DRC), Ethiopia, Ghana, Guinea, Haiti, Kenya, Liberia, Madagascar, Malawi, Mali, Nigeria, Senegal, Sierra Leone, Somalia, and Uganda). An interrupted time-series design was used to estimate the percent change in the volumes of outpatient consultations and maternal and child health services delivered during the pandemic compared to projected volumes based on prepandemic trends. The Lives Saved Tool mathematical model was used to project the impact of the service utilization disruptions on child and maternal mortality. In addition, the estimated monthly disruptions were also correlated to the monthly number of COVID-19 deaths officially reported, time since the start of the pandemic, and relative severity of mobility restrictions. Across the 18 countries, we estimate an average decline in OPD volume of 13.1% and average declines of 2.6% to 4.6% for maternal and child services. We projected that decreases in essential health service utilization between March 2020 and June 2021 were associated with 113,962 excess deaths (110,686 children under 5, and 3,276 mothers), representing 3.6% and 1.5% increases in child and maternal mortality, respectively. This excess mortality is associated with the decline in utilization of the essential health services included in the analysis, but the utilization shortfalls vary substantially between countries, health services, and over time. The largest disruptions, associated with 27.5% of the excess deaths, occurred during the second quarter of 2020, regardless of whether countries reported the highest rate of COVID-19-related mortality during the same months. There is a significant relationship between the magnitude of service disruptions and the stringency of mobility restrictions. The study is limited by the extent to which administrative data, which varies in quality across countries, can accurately capture the changes in service coverage in the population.ConclusionsDeclines in healthcare utilization during the COVID-19 pandemic amplified the pandemic’s harmful impacts on health outcomes and threaten to reverse gains in reducing maternal and child mortality. As efforts and resource allocation toward prevention and treatment of COVID-19 continue, essential health services must be maintained, particularly in low- and middle-income countries.

Tashrik Ahmed and co-workers study health-care use and maternal and child health outcomes across low- and lower-middle-income countries during the COVID-19 pandemic.     

Physical mobility under stay-at-home orders: A comparative analysis of movement restrictions between the U.S. and Europe

During the COVID-19 pandemic, both the U.S. and Europe have issued movement restrictions with the exception of visits to essential services, including groceries and pharmacies. Using Google's data on community mobility, I employ an event-study design to compare the effects of movement restrictions on physical mobility in the U.S. and Europe. I find that compared to Europe, the U.S. has higher levels of mobility related to visits to groceries and pharmacies and lower levels of the residential presence relative to baseline values, and the differences are not only statistically significant but also of large magnitudes. Such differences in post-restriction mobility are still significant between Europe and the U.S.’ early epicenters of COVID-19. The main results of this paper are robust to changes in samples and specifications. These findings suggest that movement restrictions appear to be less effective in the U.S., which have useful implications for health policy evaluation, pandemic forecasting, and economic recovery.     

基于地理信息系统的重庆地区COVID-19疫情空间分布格局演化

探讨重庆地区COVID-19疫情时空分布特征及扩散模式,以期未来为本地应对公共卫生应急事件积累经验。本文收集重庆市卫生健康委员会公布的官方数据,采用ArcGIS 10.2软件进行空间计量分析,并实现区域分布可视化,描述性统计和社会因素相关分析采用SPSS 20.0和Graphpad Prism 7.0软件进行统计和作图。结果5个时间节点,重庆地区COVID-19累计报告发病率的Moran’s I值均为正值(均P<0.05);局部Getis-ord Gi*指数分析探测到渝东北高渝东南低的态势越发明显;标准差椭圆展布呈现东北-西南的空间格局,随时间的变化经历了扩散-极化-扩散-稳定的过程;重心走势呈现向西南(渝西片区)移动距离逐渐减弱态势,市内出行(r=0.449,P=0.007)和交通网络(rs=0.321,P=0.049)对COVID-19的流行具有正相关性。重庆地区COVID-19疫情存在空间聚集性,高发聚集区域集中在渝东北片区,GIS较好地揭示了疫情聚集性变化过程和传播的时空趋势,市内出行和交通网络2个社会因素对重庆地区疫情影响较大。     

COVID-19 pandemic lockdown-induced altered sleep/wake circadian rhythm,health complaints and stress among traffic police personnel in India

ABSTRACT

COVID-19 is a highly contagious disease caused by Severe Acute Respiratory Syndrome coronavirus-2, capable of high human transmission. To protect against the COVID-19 pandemic, the World Health Organization proposed intervening guidance that included movement restrictions, isolation, restriction of national and international travel or movement, and full or partial closure of organizations and institutions. Police personnel play a vital role in safeguarding the spread of COVID-19; thus, potentially causing severe stress due to increased consignment and direct exposure to infection during duty. The study aimed to determine the effect of the added stress of the COVID-19 pandemic and population lockdown on the sleep/wake 24 h rhythm of traffic police. A concise online questionnaire survey was conducted among the traffic police personnel of India. Collected data were analyzed statistically. Disorientation of working schedule, fear of being vulnerable to disease, pressure of maintaining law, and orders during lockdown increased stress level. The survey identified discontinuation of sleep, shift of mid-sleep time, increase in depression, plus stress and anxiety among traffic police personnel that affected their chronobiological milieu. Proper awareness of adequate health and safety measures, use of personnel protection equipment, regular conversation with family members, and meditation can help reduce stress during this pandemic situation.     

Determining travel fluxes in epidemic areas

Infectious diseases attack humans from time to time and threaten the lives and survival of people all around the world. An important strategy to prevent the spatial spread of infectious diseases is to restrict population travel. With the reduction of the epidemic situation, when and where travel restrictions can be lifted, and how to organize orderly movement patterns become critical and fall within the scope of this study. We define a novel diffusion distance derived from the estimated mobility network, based on which we provide a general model to describe the spatiotemporal spread of infectious diseases with a random diffusion process and a deterministic drift process of the population. We consequently develop a multi-source data fusion method to determine the population flow in epidemic areas. In this method, we first select available subregions in epidemic areas, and then provide solutions to initiate new travel flux among these subregions. To verify our model and method, we analyze the multi-source data from mainland China and obtain a new travel flux triggering scheme in the selected 29 cities with the most active population movements in mainland China. The testable predictions in these selected cities show that reopening the borders in accordance with our proposed travel flux will not cause a second outbreak of COVID-19 in these cities. The finding provides a methodology of re-triggering travel flux during the weakening spread stage of the epidemic.     

Fathers matter: Intrahousehold responsibilities and children's wellbeing during the COVID-19 lockdown in Italy

The lockdown imposed during the spring of 2020 as a result of the COVID-19 pandemic upset families lives, in addition to the health consequences of the virus, forcing parents to completely reorganize their labor, domestic work and childcare time. At the same time, school closures forced children to rearrange their lives and learning processes: in Italy, schools and nurseries were closed for four months, and the incidence and quality of distance learning activities was heterogeneous across education levels and among schools. Using real-time survey data on families with under-16 children collected in April 2020, which include information on parents’ market and household work, and their perception of their children's wellbeing, we estimate how the lockdown has affected children's use of time, their emotional status and their home learning, and whether the reallocation of intrahousehold responsibilities during the lockdown played a role in this process. Changes in the parental division of household tasks and childcare, mostly induced by the labor market restrictions imposed during the lockdown, point to a greater involvement of fathers in childcare and homeschooling activities. This positive variation in fathers’ involvement is accompanied by an increase in children's emotional wellbeing and by a reduction in TV and passive screen time. On the other hand, the quality of children's home learning does not appear to depend on which parent is overseeing their work, but rather on the type of distance learning activities proposed by their teachers.     

The effect of income support programs on job search,workplace mobility and COVID-19: International evidence

This study examines the effect of Income Support Programs (ISPs) on job search effort, work- place mobility, COVID-19 cases, and mortality growth rates. To identify ISPs’ causal effect, I use the variation in their introductions’ timing across countries and implement a difference-in-difference and multi-event analysis method. I find that ISPs led to a 4.4–8.29 percentage points reduction in workplace mobility and a 6.6–11.6 percentage points reduction in job search effort levels. They also caused a 21.8–47.7 and 17.1–29.7 percentage points reduction in the COVID-19 case growth rate and COVID-19 mortality growth rates, respectively. Using the event analysis estimates, I simulated the counterfactual job search effort, workplace mobility, and the number of COVID-19 cases and mortality without income support programs. The average global job search effort and workplace mobility without ISPs would have been 11.12 and 9.26 percent higher than the observed mean job search effort and workplace mobility. However, these would have come at the cost of 3.69 million and 166, 690 additional COVID-19 cases and mortality than the cases and deaths registered by May 15th.     

Trusting the Health System and COVID 19 Restriction Compliance

We examine the extent to which exposure to higher relative COVID-19 mortality (RM), influences health system trust (HST), and whether changes in HST explain the perceived ease of compliance with pandemic restrictions during the COVID-19 pandemic. Drawing on evidence from two representative surveys covering all regions of 28 European countries before and after the first COVID-19 wave, and using a difference in differences strategy together with Coarsened Exact Matching (CEM), we document that living in a region with higher RM during the first wave of the pandemic increased HST. However, the positive effect of RM on HST is driven by individuals over 45 years of age, and the opposite effect is found among younger cohorts. Furthemore, we find that a higher HST reduces the costs of complying with COVID-19 restrictions, but only so long as excess mortality does not exceed the average by more than 20%, at which point the ease of complying with COVID-19 restrictions significantly declines, offsetting the positive effect of trust in the healthcare system. Our interpretation of these estimates is that a higher RM is interpreted as a risk signal among those over 45, and as a signal of health-care system failure among younger age individuals.     

Interplay between mobility,multi-seeding and lockdowns shapes COVID-19 local impact

Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. While many factors affect disease incidence at a local level, making it more or less homogeneous with respect to other areas, the importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible population. This can lead to independent outbreaks that spark from distinct areas of the local contact (social) network. Such mechanism has the potential to boost incidence, making control efforts and contact tracing less effective. Here, through a modeling approach we show that the effect produced by the number of initial infections is non-linear on the incidence peak and peak time. When case importations are carried by mobility from an already infected area, this effect is further enhanced by the local demography and underlying mixing patterns: the impact of every seed is larger in smaller populations. Finally, both in the model simulations and the analysis, we show that a multi-seeding effect combined with mobility restrictions can explain the observed spatial heterogeneities in the first wave of COVID-19 incidence and mortality in five European countries. Our results allow us for identifying what we have called epidemic epicenter: an area that shapes incidence and mortality peaks in the entire country. The present work further clarifies the nonlinear effects that mobility can have on the evolution of an epidemic and highlight their relevance for epidemic control.     

Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance,virologic testing,and mortality data: Four complementary approaches

Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the prevalence of COVID-19 across the United States (US). Equipment shortages and varying testing capabilities have however hindered the usefulness of the official reported positive COVID-19 case counts. We introduce four complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 in each state in the US as well as Puerto Rico and the District of Columbia, using a combination of excess influenza-like illness reports, COVID-19 test statistics, COVID-19 mortality reports, and a spatially structured epidemic model. Instead of relying on the estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our four approaches emerges the consistent conclusion that on April 4, 2020, the estimated case count was 5 to 50 times higher than the official positive test counts across the different states. Nationally, our estimates of COVID-19 symptomatic cases as of April 4 have a likely range of 2.3 to 4.8 million, with possibly as many as 7.6 million cases, up to 25 times greater than the cumulative confirmed cases of about 311,000. Extending our methods to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 4.9 to 10.1 million, as opposed to 1.5 million positive test counts. The proposed combination of approaches may prove useful in assessing the burden of COVID-19 during resurgences in the US and other countries with comparable surveillance systems.     

Relaxing restrictions at the pace of vaccination increases freedom and guards against further COVID-19 waves

Mass vaccination offers a promising exit strategy for the COVID-19 pandemic. However, as vaccination progresses, demands to lift restrictions increase, despite most of the population remaining susceptible. Using our age-stratified SEIRD-ICU compartmental model and curated epidemiological and vaccination data, we quantified the rate (relative to vaccination progress) at which countries can lift non-pharmaceutical interventions without overwhelming their healthcare systems. We analyzed scenarios ranging from immediately lifting restrictions (accepting high mortality and morbidity) to reducing case numbers to a level where test-trace-and-isolate (TTI) programs efficiently compensate for local spreading events. In general, the age-dependent vaccination roll-out implies a transient decrease of more than ten years in the average age of ICU patients and deceased. The pace of vaccination determines the speed of lifting restrictions; Taking the European Union (EU) as an example case, all considered scenarios allow for steadily increasing contacts starting in May 2021 and relaxing most restrictions by autumn 2021. Throughout summer 2021, only mild contact restrictions will remain necessary. However, only high vaccine uptake can prevent further severe waves. Across EU countries, seroprevalence impacts the long-term success of vaccination campaigns more strongly than age demographics. In addition, we highlight the need for preventive measures to reduce contagion in school settings throughout the year 2021, where children might be drivers of contagion because of them remaining susceptible. Strategies that maintain low case numbers, instead of high ones, reduce infections and deaths by factors of eleven and five, respectively. In general, policies with low case numbers significantly benefit from vaccination, as the overall reduction in susceptibility will further diminish viral spread. Keeping case numbers low is the safest long-term strategy because it considerably reduces mortality and morbidity and offers better preparedness against emerging escape or more contagious virus variants while still allowing for higher contact numbers (freedom) with progressing vaccinations.     

Pandemic-associated mobility restrictions could cause increases in dengue virus transmission

BackgroundThe COVID-19 pandemic has induced unprecedented reductions in human mobility and social contacts throughout the world. Because dengue virus (DENV) transmission is strongly driven by human mobility, behavioral changes associated with the pandemic have been hypothesized to impact dengue incidence. By discouraging human contact, COVID-19 control measures have also disrupted dengue vector control interventions, the most effective of which require entry into homes. We sought to investigate how and why dengue incidence could differ under a lockdown scenario with a proportion of the population sheltered at home.Methodology & principal findingsWe used an agent-based model with a realistic treatment of human mobility and vector control. We found that a lockdown in which 70% of the population sheltered at home and which occurred in a season when a new serotype invaded could lead to a small average increase in cumulative DENV infections of up to 10%, depending on the time of year lockdown occurred. Lockdown had a more pronounced effect on the spatial distribution of DENV infections, with higher incidence under lockdown in regions with higher mosquito abundance. Transmission was also more focused in homes following lockdown. The proportion of people infected in their own home rose from 54% under normal conditions to 66% under lockdown, and the household secondary attack rate rose from 0.109 to 0.128, a 17% increase. When we considered that lockdown measures could disrupt regular, city-wide vector control campaigns, the increase in incidence was more pronounced than with lockdown alone, especially if lockdown occurred at the optimal time for vector control.Conclusions & significanceOur results indicate that an unintended outcome of lockdown measures may be to adversely alter the epidemiology of dengue. This observation has important implications for an improved understanding of dengue epidemiology and effective application of dengue vector control. When coordinating public health responses during a syndemic, it is important to monitor multiple infections and understand that an intervention against one disease may exacerbate another.     

No evidence of fetal defects or anti-syncytin-1 antibody induction following COVID-19 mRNA vaccination

The impact of Coronavirus Disease 2019 (COVID-19) mRNA vaccination on pregnancy and fertility has become a major topic of public interest. We investigated 2 of the most widely propagated claims to determine (1) whether COVID-19 mRNA vaccination of mice during early pregnancy is associated with an increased incidence of birth defects or growth abnormalities; and (2) whether COVID-19 mRNA-vaccinated human volunteers exhibit elevated levels of antibodies to the human placental protein syncytin-1. Using a mouse model, we found that intramuscular COVID-19 mRNA vaccination during early pregnancy at gestational age E7.5 did not lead to differences in fetal size by crown-rump length or weight at term, nor did we observe any gross birth defects. In contrast, injection of the TLR3 agonist and double-stranded RNA mimic polyinosinic-polycytidylic acid, or poly(I:C), impacted growth in utero leading to reduced fetal size. No overt maternal illness following either vaccination or poly(I:C) exposure was observed. We also found that term fetuses from these murine pregnancies vaccinated prior to the formation of the definitive placenta exhibit high circulating levels of anti-spike and anti-receptor-binding domain (anti-RBD) antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) consistent with maternal antibody status, indicating transplacental transfer in the later stages of pregnancy after early immunization. Finally, we did not detect increased levels of circulating anti-syncytin-1 antibodies in a cohort of COVID-19 vaccinated adults compared to unvaccinated adults by ELISA. Our findings contradict popular claims associating COVID-19 mRNA vaccination with infertility and adverse neonatal outcomes.

The impact of COVID-19 mRNA vaccination on pregnancy and fertility has become a major topic of public interest. This study shows that after inoculation of pregnant mice with COVID mRNA vaccines, no birth defects or growth restrictions were found, and no induction of anti-syncytin-1 antibodies was detected in a longitudinal human cohort compared to unvaccinated volunteers.     

The impact of COVID–19 lockdown on dengue transmission in Sri Lanka; A natural experiment for understanding the influence of human mobility

BackgroundDengue is one of the major public health problems in Sri Lanka. Its outbreak pattern depends on a multitude of drivers, including human mobility. Here we evaluate the impact of COVID–19 related mobility restriction (lockdown) on the risk of dengue in Sri Lanka.MethodologyTwo-stage hierarchical models were fitted using an interrupted time-series design based on the notified dengue cases, January 2015 to July 2020. In the first stage model, the district level impact was estimated using quasi-Poisson regression models while accounting for temporal trends. Estimates were pooled at zonal and national levels in the second stage model using meta-analysis. The influence of the extended period of school closure on dengue in children in the western province was compared to adults.FindingsStatistically significant and homogeneous reduction of dengue risk was observed at all levels during the lockdown. Overall an 88% reduction in risk (RR 0.12; 95% CI from 0.08 to 0.17) was observed at the national level. The highest impact was observed among children aged less than 19 years showing a 92% reduction (RR 0.8; 95% CI from 0.03 to 0.25). We observed higher impact in the dry zone having 91% reduction (RR 0.09; 95% CI from 0.05 to 0.15) compared to wet zone showing 83% reduction (RR 0.17; 95% CI from 0.09 to 0.30). There was no indication that the overall health-seeking behaviour for dengue had a substantial influence on these estimates.SignificanceThis study offers a broad understanding of the change in risk of dengue during the COVID–19 pandemic and associated mobility restrictions in Sri Lanka. The analysis using the mobility restrictions as a natural experiment suggests mobility patterns to be a very important driver of dengue transmission.     

COVID-19 and children: medical impact and collateral damage

Children mostly experience mild SARS-CoV-2 infections, but the extent of paediatric COVID-19 disease differs between geographical regions and the distinct pandemic waves. Not all infections in children are mild, some children even show a strong inflammatory reaction resulting in a multisystem inflammatory syndrome. The assessments of paediatric vaccination depend on the efficacy of protection conferred by vaccination, the risk of adverse reactions and whether children contribute to herd immunity against COVID-19. Children were also the target of consequential public health actions such as school closure which caused substantial harm to children (educational deficits, sociopsychological problems) and working parents. It is, therefore, important to understand the transmission dynamics of SARS-CoV-2 infections by children to assess the efficacy of school closures and paediatric vaccination. The societal restrictions to contain the COVID-19 pandemic had additional negative effects on children’s health, such as missed routine vaccinations, nutritional deprivation and lesser mother–child medical care in developing countries causing increased child mortality as a collateral damage. In this complex epidemiological context, it is important to have an evidence-based approach to public health approaches. The present review summaries pertinent published data on the role of children in the pandemic, whether they are drivers or followers of the infection chains and whether they are (after elderlies) major sufferers or mere bystanders of the COVID-19 pandemic.