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The impact of stay-at-home orders on the rate of emergency department child maltreatment diagnoses
research-article
Publication date (Electronic):
6 August 2022
Journal:
Child Abuse & Neglect
Publisher:
Elsevier Ltd.
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Abstract
Background
There is limited data regarding the rates and severity of child maltreatment in medical settings during the COVID-19 pandemic, and the reports are somewhat contradictory.
Objective
To examine the rates of emergency department (ED) child maltreatment (CM) diagnosis before and after the California statewide stay-at-home order, as well as potential disparities by age, gender, race/ethnicity, and Medicaid status.
Methods
A retrospective pre-post interrupted time series was conducted using data from the electronic health records of children (<18 years) with at least one emergency department visit between January 1, 2019 and September 30, 2021. Enactment of the stay-at-home order in California, March 2020 was used to determine a change in trend of rates of diagnosis of CM in the ED.
Results
Overall the study included 407,228 pediatric ED visits. There was a significant change in the percentage of CM visits immediately after the stay-at-home order, followed by small month to month decreases returning to near pre-stay-at-home order levels. This significant increase was driven by higher risk for children <4 years old. The increased rate of CM in the first month after the stay-at-home order was also elevated for female, Black, and Hispanic children.
Conclusions
Our results indicated the rates of CM diagnoses in the ED doubled after the March 2020 stay-at-home order in California. Additionally, our findings suggest that some children may be at higher risk than others, which supports the importance of social safety nets for children in times of national emergency.
Related collections
Most cited references35
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Assessing Differential Impacts of COVID-19 on Black Communities
Gregorio Millett, Austin T. Jones, David Benkeser … (2020)
Purpose Given incomplete data reporting by race, we used data on COVID-19 cases and deaths in US counties to describe racial disparities in COVID-19 disease and death and associated determinants. Methods Using publicly available data (accessed April 13, 2020), predictors of COVID-19 cases and deaths were compared between disproportionately (>13%) black and all other ( 13% black residents. Conclusions Nearly twenty-two percent of US counties are disproportionately black and they accounted for 52% of COVID-19 diagnoses and 58% of COVID-19 deaths nationally. County-level comparisons can both inform COVID-19 responses and identify epidemic hot spots. Social conditions, structural racism, and other factors elevate risk for COVID-19 diagnoses and deaths in black communities.
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Impact of the COVID-19 Pandemic on Emergency Department Visits — United States, January 1, 2019–May 30, 2020
On March 13, 2020, the United States declared a national emergency to combat coronavirus disease 2019 (COVID-19). As the number of persons hospitalized with COVID-19 increased, early reports from Austria ( 1 ), Hong Kong ( 2 ), Italy ( 3 ), and California ( 4 ) suggested sharp drops in the numbers of persons seeking emergency medical care for other reasons. To quantify the effect of COVID-19 on U.S. emergency department (ED) visits, CDC compared the volume of ED visits during four weeks early in the pandemic March 29–April 25, 2020 (weeks 14 to 17; the early pandemic period) to that during March 31–April 27, 2019 (the comparison period). During the early pandemic period, the total number of U.S. ED visits was 42% lower than during the same period a year earlier, with the largest declines in visits in persons aged ≤14 years, females, and the Northeast region. Health messages that reinforce the importance of immediately seeking care for symptoms of serious conditions, such as myocardial infarction, are needed. To minimize SARS-CoV-2, the virus that causes COVID-19, transmission risk and address public concerns about visiting the ED during the pandemic, CDC recommends continued use of virtual visits and triage help lines and adherence to CDC infection control guidance. To assess trends in ED visits during the pandemic, CDC analyzed data from the National Syndromic Surveillance Program (NSSP), a collaborative network developed and maintained by CDC, state and local health departments, and academic and private sector health partners to collect electronic health data in real time. The national data in NSSP includes ED visits from a subset of hospitals in 47 states (all but Hawaii, South Dakota, and Wyoming), capturing approximately 73% of ED visits in the United States able to be analyzed at the national level. During the most recent week, 3,552 EDs reported data. Total ED visit volume, as well as patient age, sex, region, and reason for visit were analyzed. Weekly number of ED visits were examined during January 1, 2019–May 30, 2020. In addition, ED visits during two 4-week periods were compared using mean differences and ratios. The change in mean visits per week during the early pandemic period and the comparison period was calculated as the mean difference in total visits in a diagnostic category between the two periods, divided by 4 weeks ([visits in diagnostic category {early pandemic period} – visits in diagnostic category {comparison period}]/4). The visit prevalence ratio (PR) was calculated for each diagnostic category as the proportion of ED visits during the early pandemic period divided by the proportion of visits during the comparison period ([visits in category {early pandemic period}/all visits {early pandemic period}]/[visits in category {comparison period}/all visits {comparison period}]). All analyses were conducted using R software (version 3.6.0; R Foundation). Reason for visit was analyzed using a subset of records that had at least one specific, billable International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code. In addition to Hawaii, South Dakota, and Wyoming, four states (Florida, Louisiana, New York outside New York City, and Oklahoma), two California counties reporting to the NSSP (Santa Cruz and Solano), and the District of Columbia were also excluded from the diagnostic code analysis because they did not report diagnostic codes during both periods or had differences in completeness of codes between 2019 and 2020. Among eligible visits for the diagnostic code analysis, 20.3% without a valid ICD-10-CM code were excluded. ED visits were categorized using the Clinical Classifications Software Refined tool (version 2020.2; Healthcare Cost and Utilization Project), which combines ICD-10-CM codes into clinically meaningful groups ( 5 ). A visit with multiple ICD-10-CM codes could be included in multiple categories; for example, a visit by a patient with diabetes and hypertension would be included in the category for diabetes and the category for hypertension. Because COVID-19 is not yet classified in this tool, a custom category, defined as any visit with the ICD-10-CM code for confirmed COVID-19 diagnosis (U07.1), was created ( 6 ). The analysis was limited to the top 200 diagnostic categories during each period. The lowest number of visits reported to NSSP occurred during April 12–18, 2020 (week 16). Although visits have increased since the nadir, the most recent complete week (May 24–30, week 22) remained 26% below the corresponding week in 2019 (Figure 1). The number of ED visits decreased 42%, from a mean of 2,099,734 per week during March 31–April 27, 2019, to a mean of 1,220,211 per week during the early pandemic period of March 29–April 25, 2020. Visits declined for every age group (Figure 2), with the largest proportional declines in visits by children aged ≤10 years (72%) and 11–14 years (71%). Declines in ED visits varied by U.S. Department of Health and Human Services region,* with the largest declines in the Northeast (Region 1, 49%) and in the region that includes New Jersey and New York (Region 2, 48%) (Figure 2). Visits declined 37% among males and 45% among females across all NSSP EDs between the comparison and early pandemic periods. FIGURE 1 Weekly number of emergency department (ED) visits — National Syndromic Surveillance Program, United States,* January 1, 2019– May 30, 2020† * Hawaii, South Dakota, and Wyoming are not included. † Vertical lines indicate the beginning and end of the 4-week coronavirus disease 2019 (COVID-19) early pandemic period (March 29–April 25, 2020) and the comparison period (March 31–April 27, 2019). The figure is a line graph showing the weekly number of emergency department visits, using data from the National Syndromic Surveillance Program, in the United States, during January 1, 2019–May 30, 2020. FIGURE 2 Emergency department (ED) visits, by age group (A) and U.S. Department of Health and Human Services (HHS) region* (B) — National Syndromic Surveillance Program, United States,† March 31–April 27, 2019 (comparison period) and March 29–April 25, 2020 (early pandemic period) * Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont; Region 2: New Jersey and New York; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, and Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, and Texas; Region 7: Iowa, Kansas, Missouri, and Nebraska; Region 8: Colorado, Montana, North Dakota, and Utah; Region 9: Arizona, California, and Nevada; Region 10: Alaska, Idaho, Oregon, and Washington. † Hawaii, South Dakota, and Wyoming are not included. The figure is a bar chart showing the emergency department visits, by age group and U.S. Department of Health and Human Services region, using data from the National Syndromic Surveillance Program, in the United States, during March 31–April 27, 2019 (comparison period) and March 29–April 25, 2020 (pandemic period). Among all ages, an increase of >100 mean visits per week from the comparison period to the early pandemic period occurred in eight of the top 200 diagnostic categories (Table). These included 1) exposure, encounters, screening, or contact with infectious disease (mean increase 18,834 visits per week); 2) COVID-19 (17,774); 3) other general signs and symptoms (4,532); 4) pneumonia not caused by tuberculosis (3,911); 5) other specified and unspecified lower respiratory disease (1,506); 6) respiratory failure, insufficiency, or arrest (776); 7) cardiac arrest and ventricular fibrillation (472); and 8) socioeconomic or psychosocial factors (354). The largest declines were in visits for abdominal pain and other digestive or abdomen signs and symptoms (–66,456), musculoskeletal pain excluding low back pain (–52,150), essential hypertension (–45,184), nausea and vomiting (–38,536), other specified upper respiratory infections (–36,189), sprains and strains (–33,709), and superficial injuries (–30,918). Visits for nonspecific chest pain were also among the top 20 diagnostic categories for which visits decreased (–24,258). Although not in the top 20 declining diagnoses, visits for acute myocardial infarction also declined (–1,156). TABLE Differences in mean weekly numbers of emergency department (ED) visits* for diagnostic categories with the largest increases or decreases† and prevalence ratios§ comparing the proportion of ED visits in each diagnostic category, for categories with the highest and lowest ratios — National Syndromic Surveillance Program, United States,¶ March 31–April 27, 2019 (comparison period) and March 29–April 25, 2020 (early pandemic period) Diagnostic category Change in mean no. of weekly ED visits* Prevalence ratio (95% CI)§ All categories with higher visit counts during the early pandemic period Exposure, encounters, screening, or contact with infectious disease** 18,834 3.79 (3.76–3.83) COVID-19 17,774 — Other general signs and symptoms** 4,532 1.87 (1.86–1.89) Pneumonia (except that caused by tuberculosis)** 3,911 1.91 (1.90–1.93) Other specified and unspecified lower respiratory disease** 1,506 1.99 (1.96–2.02) Respiratory failure, insufficiency, arrest** 776 1.76 (1.74–1.78) Cardiac arrest and ventricular fibrillation** 472 1.98 (1.93–2.03) Socioeconomic or psychosocial factors** 354 1.78 (1.75–1.81) Other top 10 highest prevalence ratios Mental and substance use disorders, in remission** 6 1.69 (1.64–1.75) Other specified encounters and counseling** 22 1.69 (1.67–1.72) Stimulant-related disorders** −189 1.65 (1.62–1.67) Top 20 categories with lower visit counts during the early pandemic period Abdominal pain and other digestive or abdomen signs and symptoms −66,456 0.93 (0.93–0.93) Musculoskeletal pain, not low back pain −52,150 0.81 (0.81–0.82) Essential hypertension −45,184 1.11 (1.10–1.11) Nausea and vomiting −38,536 0.85 (0.84–0.85) Other specified upper respiratory infections −36,189 0.82 (0.81–0.82) Sprains and strains, initial encounter †† −33,709 0.61 (0.61–0.62) Superficial injury; contusion, initial encounter −30,918 0.85 (0.84–0.85) Personal or family history of disease −28,734 1.21 (1.20–1.22) Headache, including migraine −27,458 0.85 (0.84–0.85) Other unspecified injury −25,974 0.84 (0.83–0.84) Nonspecific chest pain −24,258 1.20 (1.20–1.21) Tobacco-related disorders −23,657 1.19 (1.18–1.19) Urinary tract infections −23,346 1.02 (1.02–1.03) Asthma −20,660 0.91 (0.90–0.91) Disorders of lipid metabolism −20,145 1.12 (1.11–1.13) Spondylopathies/Spondyloarthropathy (including infective) −19,441 0.78 (0.77–0.79) Otitis media †† −17,852 0.35 (0.34–0.36) Diabetes mellitus without complication −15,893 1.10 (1.10–1.11) Skin and subcutaneous tissue infections −15,598 1.01 (1.00–1.02) Chronic obstructive pulmonary disease and bronchiectasis −15,520 1.05 (1.04–1.06) Other top 10 lowest prevalence ratios Influenza †† −12,094 0.16 (0.15–0.16) No immunization or underimmunization †† −1,895 0.28 (0.27–0.30) Neoplasm-related encounters †† −1,926 0.40 (0.39–0.42) Intestinal infection †† −5,310 0.52 (0.51–0.54) Cornea and external disease †† −9,096 0.54 (0.53–0.55) Sinusitis †† −7,283 0.55 (0.54–0.56) Acute bronchitis †† −15,470 0.59 (0.58–0.60) Noninfectious gastroenteritis †† −11,572 0.63 (0.62–0.64) Abbreviations: CI = confidence interval; COVID-19 = coronavirus disease 2019. * The change in visits per week during the early pandemic and comparison periods was calculated as the difference in total visits between the two periods, divided by 4 weeks ([visits in diagnostic category, {early pandemic period} – visits in diagnostic category, {comparison period}] / 4). † Analysis is limited to the 200 most common diagnostic categories. All eight diagnostic categories with an increase of >100 in the mean number of visits nationwide in the early pandemic period are shown. The top 20 categories with decreasing visit counts are shown. § Ratio calculated as the proportion of all ED visits in each diagnostic category during the early pandemic period, divided by the proportion of all ED visits in that category during the comparison period ([visits in category {early pandemic period}/all visits {early pandemic period})/(visits in category {comparison period}/all visits {comparison period}]). Ratios >1 indicate a higher proportion of visits in that category during the early pandemic period than the comparison period; ratios <1 indicate a lower proportion during the early pandemic than during the comparison period. Analysis is limited to the 200 most common diagnostic categories. The 10 categories with the highest and lowest ratios are shown. ¶ Florida, Hawaii, Louisiana, New York outside of New York City, Oklahoma, South Dakota, Wyoming, Santa Cruz and Solano counties in California, and the District of Columbia are not included. ** Top 10 highest prevalence ratios; higher proportion of visits in the early pandemic period than the comparison period. †† Top 10 lowest prevalence ratios; lower proportion of visits in the early pandemic period than the comparison period. During the early pandemic period, the proportion of ED visits for exposure, encounters, screening, or contact with infectious disease compared with total visits was nearly four times as large as during the comparison period (Table) (prevalence ratio [PR] = 3.79, 95% confidence interval [CI] = 3.76–3.83). The other diagnostic categories with the highest proportions of visits during the early pandemic compared with the comparison period were other specified and unspecified lower respiratory disease, which did not include influenza, pneumonia, asthma, or bronchitis (PR = 1.99; 95% CI = 1.96–2.02), cardiac arrest and ventricular fibrillation (PR = 1.98; 95% CI = 1.93–2.03), and pneumonia not caused by tuberculosis (PR = 1.91; 95% CI = 1.90–1.93). Diagnostic categories that were recorded less commonly during the early pandemic period included influenza (PR = 0.16; 95% CI = 0.15–0.16), no immunization or underimmunization (PR = 0.28; 95% CI = 0.27–0.30), otitis media (PR = 0.35; 95% CI = 0.34–0.36), and neoplasm-related encounters (PR = 0.40; 95% CI = 0.39–0.42). In the 2019 comparison period, 12% of all ED visits were in children aged ≤10 years old, compared with 6% during the early pandemic period. Among children aged ≤10 years, the largest declines were in visits for influenza (97% decrease), otitis media (85%), other specified upper respiratory conditions (84%), nausea and vomiting (84%), asthma (84%), viral infection (79%), respiratory signs and symptoms (78%), abdominal pain and other digestive or abdomen symptoms (78%), and fever (72%). Mean weekly visits with confirmed COVID-19 diagnoses and screening for infectious disease during the early pandemic period were lower among children than among adults. Among all ages, the diagnostic categories with the largest changes (abdominal pain and other digestive or abdomen signs and symptoms, musculoskeletal pain, and essential hypertension) were the same in males and females, but declines in those categories were larger in females than males. Females also had large declines in visits for urinary tract infections (–19,833 mean weekly visits). Discussion During an early 4-week interval in the COVID-19 pandemic, ED visits were substantially lower than during the same 4-week period during the previous year; these decreases were especially pronounced for children and females and in the Northeast. In addition to diagnoses associated with lower respiratory disease, pneumonia, and difficulty breathing, the number and ratio of visits (early pandemic period versus comparison period) for cardiac arrest and ventricular fibrillation increased. The number of visits for conditions including nonspecific chest pain and acute myocardial infarction decreased, suggesting that some persons could be delaying care for conditions that might result in additional mortality if left untreated. Some declines were in categories including otitis media, superficial injuries, and sprains and strains that can often be managed through primary or urgent care. Future analyses will help clarify the proportion of the decline in ED visits that were not preventable or avoidable such as those for life-threatening conditions, those that were manageable through primary care, and those that represented actual reductions in injuries or illness attributable to changing activity patterns during the pandemic (such as lower risks for occupational and motor vehicle injuries or other infectious diseases). The striking decline in ED visits nationwide, with the highest declines in regions where the pandemic was most severe in April 2020, suggests that the pandemic has altered the use of the ED by the public. Persons who use the ED as a safety net because they lack access to primary care and telemedicine might be disproportionately affected if they avoid seeking care because of concerns about the infection risk in the ED. Syndromic surveillance has important strengths, including automated electronic reporting and the ability to track outbreaks in real time ( 7 ). Among all visits, 74% are reported within 24 hours, with 75% of discharge diagnoses typically added to the record within 1 week. The findings in this report are subject to at least four limitations. First, hospitals reporting to NSSP change over time as facilities are added, and more rarely, as they close ( 8 ). An average of 3,173 hospitals reported to NSSP nationally in April 2019, representing an estimated 66% of U.S. ED visits, and an average of 3,467 reported in April 2020, representing 73% of ED visits. Second, diagnostic categories rely on the use of specific codes, which were missing in 20% of visits and might be used inconsistently across hospitals and providers, which could result in misclassification. The COVID-19 diagnosis code was introduced recently (April 1, 2020) and timing of uptake might have differed across hospitals ( 6 ). Third, NSSP coverage is not uniform across or within all states; in some states nearly all hospitals report, whereas in others, a lower proportion statewide or only those in certain counties report. Finally, because this analysis is limited to ED visit data, the proportion of persons who did not visit EDs but received treatment elsewhere is not captured. Health care systems should continue to address public concern about exposure to SARS-CoV-2 in the ED through adherence to CDC infection control recommendations, such as immediately screening every person for fever and symptoms of COVID-19, and maintaining separate, well-ventilated triage areas for patients with and without signs and symptoms of COVID-19 ( 9 ). Wider access is needed to health messages that reinforce the importance of immediately seeking care for serious conditions for which ED visits cannot be avoided, such as symptoms of myocardial infarction. Expanded access to triage telephone lines that help persons rapidly decide whether they need to go to an ED for symptoms of possible COVID-19 infection and other urgent conditions is also needed. For conditions that do not require immediate care or in-person treatment, health care systems should continue to expand the use of virtual visits during the pandemic ( 10 ). Summary What is already known about this topic? The National Syndromic Surveillance Program (NSSP) collects electronic health data in real time. What is added by this report? NSSP found that emergency department (ED) visits declined 42% during the early COVID-19 pandemic, from a mean of 2.1 million per week (March 31–April 27, 2019) to 1.2 million (March 29–April 25, 2020), with the steepest decreases in persons aged ≤14 years, females, and the Northeast. The proportion of infectious disease–related visits was four times higher during the early pandemic period. What are the implications for public health practice? To minimize SARS-CoV-2 transmission risk and address public concerns about visiting the ED during the pandemic, CDC recommends continued use of virtual visits and triage help lines and adherence to CDC infection control guidance.
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Mitigating the wider health effects of covid-19 pandemic response
Countries worldwide have implemented strict controls on movement in response to the covid-19 pandemic. The aim is to cut transmission by reducing close contact (box 1), but the measures have profound consequences. Several sectors are seeing steep reductions in business, and there has been panic buying in shops. Social, economic, and health consequences are inevitable. Box 1 Social distancing measures Advising the whole population to self-isolate at home if they or their family have symptoms Bans on social gatherings (including mass gatherings) Stopping flights and public transport Closure of “non-essential” workplaces (beyond the health and social care sector, utilities, and the food chain) with continued working from home for those that can Closure of schools, colleges, and universities Prohibition of all “non-essential” population movement Limiting contact for special populations (eg, care homes, prisons) The health benefits of social distancing measures are obvious, with a slower spread of infection reducing the risk that health services will be overwhelmed. But they may also prolong the pandemic and the restrictions adopted to mitigate it.1 Policy makers need to balance these considerations while paying attention to broader effects on health and health equity. Who is most at risk? Several groups may be particularly vulnerable to the effects of both the pandemic and the social distancing measures (box 2). Table 1 summarises several mechanisms through which the pandemic response is likely to affect health: economic effects, social isolation, family relationships, health related behaviours, disruption to essential services, disrupted education, transport and green space, social disorder, and psychosocial effects. Figure 1 shows the complexity of the pathways through which these effects may arise. Below we expand on the first three mechanisms, using Scotland as an example. The appendix on bmj.com provides further details of mechanisms, effects, and mitigation measures. Box 2 Groups at particular risk from responses to covid-19 Older people—highest direct risk of severe covid-19, more likely to live alone, less likely to use online communications, at risk of social isolation Young people—affected by disrupted education at critical time; in longer term most at risk of poor employment and associated health outcomes in economic downturn Women—more likely to be carers, likely to lose income if need to provide childcare during school closures, potential for increase in family violence for some People of East Asian ethnicity—may be at increased risk of discrimination and harassment because the pandemic is associated with China People with mental health problems—may be at greater risk from social isolation People who use substances or in recovery—risk of relapse or withdrawal People with a disability—affected by disrupted support services People with reduced communication abilities (eg, learning disabilities, limited literacy or English language ability)—may not receive key governmental communications Homeless people—may be unable to self-isolate or affected by disrupted support services People in criminal justice system—difficulty of isolation in prison setting, loss of contact with family Undocumented migrants—may have no access to or be reluctant to engage with health services Workers on precarious contracts or self-employed—high risk of adverse effects from loss of work and no income People on low income—effects will be particularly severe as they already have poorer health and are more likely to be in insecure work without financial reserves People in institutions (care homes, special needs facilities, prisons, migrant detention centres, cruise liners)—as these institutions may act as amplifiers Table 1 Health effects of social distancing measures and actions to mitigate them Mechanism Summary of effects Summary of mitigations Economic effects • Income losses for workers unable to work• Longer term increase in unemployment if businesses fail• Recession • Protect incomes at the level of the minimum income for healthy living• Provide food and other essential supplies• Reduce longer term unemployment• Prioritise inclusive and sustainable economic development during recovery Social isolation • Lack of social contact, particularly for people who live alone and have less access to digital connectivity• Difficulty accessing food and other supplies • Encourage and support other forms of social contact• Provide supplies• Provide clear communications• Restrict duration of isolation Family relationships • Home confinement may increase family violence and abuse• Potential exploitation of young people not in school • Offer support to vulnerable families• Ensure realistic expectations for home working and home schooling• Provide safety advice and support services for women at risk of domestic abuse Health related behaviours • Potential for increased substance use, increased online gambling, and a rise in unintended pregnancies• Reduction in physical activity as sports facilities closed and less utilitarian walking and cycling • Advice and support on substance use, gambling, contraception• Encourage daily physical activity Disruption to essential services • Direct effects on health and social care demand• Unwillingness to attend healthcare settings may affect care of other conditions• Loss of workforce may affect essential services • Robust business continuity planning• Prioritise essential services including healthcare, social care, emergency services, utilities, and the food chain• Guidance, online consultations, and outreach, for conditions other than covid-19• Attention to supply chains for non-covid medicines Disruption to education • Loss of education and skills, particularly for young people at critical transitions• Likely increase in educational inequalities from reliance on home schooling • Provide support for young people in critical transitions, and low income or at-risk children and young people who lack IT and good home study environments Traffic, transport, and green space • Reduced aviation and motorised traffic with reduced air pollution, noise, injuries, and carbon emissions in short term• Restricted public transport may reduce access for people without a car• Longer term reluctance to use public transport may increase use of private cars• Restricted access to green space, which has benefits for physical and mental health • Discourage unnecessary car journeys• Support active travel modes• Support safe access to green spaces• Post-pandemic support for public transport Social disorder • Potential for unrest if supplies run out or there is widespread discontent about the response• Harassment of people believed to be at risk of transmitting the virus • Mitigation of other effects will reduce risk of social disorder• Avoid stigmatising ill people or linking the pandemic to specific populations Psychosocial impacts • High level of public fear and anxiety• Community cohesion could increase as people respond collectively • Provide clear communications• Support community organisations responding to local needs Fig 1 Effects of social distancing measures on health Economic effects People may experience loss of income from social distancing in several ways. Although some people can work at home, many cannot, especially those in public facing roles in service industries, a group that already faces precarious employment and low income.2 Others may be affected by workplace closures, caused by government mandate, an infected co-worker, or loss of business. Yet more may be unable to work as school closures require them to provide childcare. In the UK, 3.5 million additional people are expected to need universal credit (which includes unemployment payments) as a result of the pandemic.3 The growth of the informal, gig economy in some countries has created a large group of people who are especially vulnerable as they do not get sick pay, are on zero hours contracts, or are self-employed.4 They can easily lose all their income, and even if this is only temporary they often lack the safety net of savings. An important risk is housing security, with loss of income causing rent or mortgage arrears or even homelessness. School closure will affect low income and single parent families especially severely because they need to meet an unexpected need for childcare and lose the benefit of free school meals. They may also face increased costs for heating their homes during the day. In some countries, welfare systems impose strict conditions on recipients that cannot be met by those in isolation. The link between income and health is well established and acts through several mechanisms.5 Income allows people to buy necessities for life, access health enhancing resources, avoid harmful exposures, and participate in normal activities of society. Low income also increases psychosocial stress. The minimum income for healthy living establishes a standard required to maintain health in different settings.6 Crucially, not everyone is equally likely to lose income. Women, young people, and those who are already poor will fare worst. To avoid widening health inequalities, social distancing must be accompanied by measures to safeguard the incomes of poor people. Future challenges The longer term effects may be substantial. If businesses fail, many employees will become unemployed. Those losing their jobs in middle age may never return to the workforce. Sectors that are especially vulnerable include hospitality, entertainment, transport, leisure, and sport. Unemployment has large negative effects on both physical and mental health,7 with a meta-analysis reporting a 76% increase in all-cause mortality in people followed for up to 10 years after becoming unemployed.8 The pandemic has already caused downgrading of economic forecasts, with many countries facing a recession. The health consequences of a recession are complex. Economic downturns have been associated with improvements in some health outcomes, especially traffic injuries, but worsening mental health, including increases in homicide and suicide.9 However, these harmful effects can be prevented by progressive social policies; it is the policy response to a recession, rather than the recession itself, that determines longer term population health.10 Throughout history, some people have viewed any crisis as an opportunity. Klein described how “disaster capitalists” take advantage of natural and human influenced disasters.11 There is clear potential for price gouging (profiteering through increased prices during supply or demand shocks) on essential goods. Once the pandemic recedes, there could be profound changes to the economy that may disadvantage less powerful populations, such as through privatisation of public sector services. However, there may also be opportunities for the economy to be rebuilt “better,” depending on public and political attitudes and power balance.12 Social isolation Advising or compelling people to self-isolate at home risks serious social and psychological harm. Quarantine of people exposed to an infectious disease is associated with negative psychological effects, including post-traumatic stress symptoms, which may be long lasting.13 The effects are exacerbated by prolonged isolation, fear of the infection, frustration, boredom, inadequate supplies and information, financial loss, and stigma. These effects are less when quarantine is voluntary and can be mitigated by ensuring clear rapid communication, keeping the duration short, providing food and other essential supplies, and protecting against financial loss.13 In Scotland, a third of the population lives alone and 40% of this group are of pensionable age.14 Older people are also less likely to use online communications, making them at particular risk of social isolation during social distancing. Social isolation is defined as pervasive lack of social contact or communication, participation in social activities, or a confidante. Long term, social isolation is associated with an increase in mortality of almost a third.15 Prolonged periods of social distancing could have similar effects. People who are socioeconomically disadvantaged or in poor physical or mental health are at higher risk.16 Online and telephone support needs to be provided for vulnerable groups, especially those living alone. Family relationships Social distancing measures will place many people in close proximity with family members all or most of the time, which may cause or exacerbate tensions. Concern has been raised about potential increases in family violence during restrictions in the UK.17 Risk factors for partner and child abuse include poverty, substance misuse in the home, and previous history of abuse.18 19 Around 60 000 domestic abuse incidents occur in Scotland every year, with young women most affected, 20 and over 2500 children are on the child protection register.21 It is important to maintain social work and community support for vulnerable families, including safety advice for women at risk of abuse. Domestic abuse advocates have called for enhanced support, including allocation of hotel rooms for women at risk.17 School closures may add to stress in families as parents try to home school children, often juggling this with home working. This burden may fall disproportionately on women. As well as academic learning, schools support development of social and other skills. Prolonged school closures could cause adverse effects on educational and social outcomes for young people in families that lack study space and access to home computing.22 Some children who are not at school may be at risk of online or other forms of exploitation—for example, by drug dealers—or of being recruited into gangs. Realistic expectations of home schooling, provision of food for those eligible for free school meals, and outreach support for the most vulnerable children will be needed during school closures. Many children will need extra support on return to school.22 Mitigating adverse effects In addition to the direct disease burden from covid-19, the pandemic response is already causing negative indirect effects such as those described above. These are borne disproportionately by people who already have fewer resources and poorer health. Prolonged or more restrictive social distancing measures could increase health inequalities in the short and long term. Our assessment is based on rapid scoping of potential impacts and a non-systematic review of diverse publications, so there is a high degree of uncertainty about the extent of some impacts. However, the range of health concerns identified, beyond those directly attributable to the virus itself, should be recognised in developing and implementing responses. The effects may also vary by context. In low and middle income countries without social safety nets, the effects on population health and health inequalities are likely to be worse than in richer countries, as is beginning to be seen in India.23 Actions must be targeted to support the most vulnerable people. The extraordinary measures in the UK to allow businesses to continue paying staff will help mitigate the harms for many workers. But it is important to consider people in precarious work who will not be covered by these measures, and to consider longer term support for those who continue to experience problems once the measures expire. A large multiagency response will be needed to deal with the wide range of needs we have identified. In the longer term, policy decisions made now will shape the future economy in ways that could either improve or damage sustainability, health, and health inequalities. These include decisions about which sectors to prioritise for support, whether to direct financial support to business or workers, and how to fund the costs. To protect population health it will be essential to avoid a further period of austerity and the associated reductions in social security and public service spending. Instead we must build a more sustainable and inclusive economy.10 Key messages Social distancing measures to control the spread of covid-19 are likely to have large effects on health and health inequalities These effects have numerous mechanisms, including economic, social, health related behaviours, and disruption to services and education People on low incomes are most vulnerable to the adverse effects Substantial mitigation measures are needed in the short and long term
Author and article information
Journal
Journal ID (nlm-ta): Child Abuse Negl
Journal ID (iso-abbrev): Child Abuse Negl
Title:
Child Abuse & Neglect
Publisher:
Elsevier Ltd.
ISSN
(Print):
0145-2134
ISSN
(Electronic):
1873-7757
Publication date PMC-release: 6
August
2022
Publication date
(Print):
October
2022
Publication date
(Electronic):
6
August
2022
Volume: 132
Page: 105821
Affiliations
[a
]Kaiser Permanente Southern California, Department of Research & Evaluation, Pasadena,
CA, United States of America
Author notes
Article
Publisher Item ID: S0145-2134(22)00355-6 Publisher ID: 105821DOI: 10.1016/j.chiabu.2022.105821
PMC ID: 9355635
PubMed ID: 35939889
SO-VID: 920957c3-d0af-42c0-a883-361b1d122a80
Copyright © © 2022 Elsevier Ltd. All rights reserved.
License:
Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
History
Date
received
: 14
March
2022
Date
revision received
: 18
July
2022
Date
accepted
: 26
July
2022
Categories
Subject:
Article
Data availability: