Background: Injectable interferon-based therapies have been used to treat hepatitis C virus (HCV) infection since 1991. International guidelines have now moved away from interferon-based therapy towards direct-acting antiviral (DAA) tablet regimens, because of their superior efficacy, excellent side-effect profiles, and ease of administration. Initially DAA drugs were prohibitively expensive for most healthcare systems. Access is now improving through the procurement of low-cost, generic DAAs acquired through voluntary licenses. However, HCV treatment costs vary widely, and many countries are struggling with DAA treatment scale-up. This is not helped by the limited cost data and economic evaluations from low- and middle-income countries to support HCV policy decisions. We conducted a detailed analysis of the costs of treating chronic HCV infection with interferon-based therapy in Vietnam. Understanding these costs is important for performing necessary economic evaluations of novel treatment strategies.Methods: We conducted an analysis of the direct medical costs of treating HCV infection with interferon alpha (IFN) and pegylated-interferon alpha (Peg-IFN), in combination with ribavirin, from the health sector perspective at the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam, in 2017.Results: The total cost of the IFN treatment regimen was estimated to range between US$1,120 and US$1,962. The total cost of the Peg-IFN treatment regimen was between US$2,156 and US$5,887. Drug expenses were the biggest contributor to the total treatment cost (54-89%) and were much higher for the Peg-IFN regimen.Conclusions: We found that treating HCV with IFN or Peg-IFN resulted in significant direct medical costs. Of concern, we found that all patients incurred substantial out-of-pocket costs, including those receiving the maximum level of support from the national health insurance programme. This cost data highlights the potential savings and importance of increased access to generic DAAs in low- and middle-income countries and will be useful within future economic evaluations. Hepatitis C virus (HCV) is typically transmitted through intravenous drug use, unsafe injection practice and the transfusion of unscreened blood/blood products1. There are six major HCV strains, genotypes 1–6, and the prevalence of each genotype varies significantly between regions1. Currently, most data relate to the treatment of genotypes 1–4; few data exist regarding the treatment outcomes and costs of genotype 6 infection, which accounts for over 50% of HCV infections in Vietnam2.The World Health Organization (WHO) estimates that there are 71 million people living with chronic hepatitis C infection globally3. The original interferon (IFN) intramuscular injections had to be administered daily and were associated with poor cure rates and unpleasant side effects4. Pegylated IFN (Peg-IFN) was first licensed in 20015 and has improved pharmacokinetics, requiring only weekly injections. Additionally, Peg-IFN is more effective than IFN and is associated with fewer adverse effects6. When used for 24–48 weeks with the anti-viral tablet ribavirin, Peg-IFN is associated with cure rates of 54–63% 7. In recent years, new oral direct-acting antivirals (DAAs) have been developed. DAA therapy requires a shorter duration of treatment  and has superior cure rates to interferon-based therapy (>95%)8. The tablets have almost no side effects and forgo the need for weekly injections9. When they first emerged, DAA drugs were prohibitively expensive for many healthcare systems, making them unavailable in most low- and lower-middle-income countries. Whilst prices still restrict access in many settings, the situation is improving, with steep price reductions for DAAs, driven largely by increased competition from generic manufacturers and the issuing of voluntary licenses10. In 2016, 86% of people starting HCV therapy worldwide received DAA drugs rather than interferon-based therapy11. Recently, the WHO recommended that interferon-based therapy should no longer be used where DAA drugs are available8.Interferon-based therapies have been used to treat HCV since 199112. The specific goals set for hepatitis C were that 80% of patients are treated, along with a 90% reduction in the incidence and a 65% reduction in HCV related mortality12. In 2015, only 7% of the 71 million people living with chronic HCV infection were treated12. Therefore, access to treatment needs to expand if the elimination goals are to be achieved.In 2016, the WHO released the first Global Health Sector Strategy on viral hepatitis with a goal of eliminating viral hepatitis as a public health threat by 203011. A WHO analysis of country experiences of DAA scale-up shows that, while access to affordable treatment is important, countries also need a strong government response, including national plans for preventing, diagnosing and treating HCV, and adequate financing to roll out and sustain HCV services13. For this to occur, it is vital to have a detailed understanding of the cost and cost-effectiveness of the different treatment options available in low- and middle-income countries15.Although improving, the global scale-up of DAA treatment has been markedly uneven, with a handful of countries  accounting for the majority of the increase in uptake16. Consequently, due to its side effect profile and the increasing availability of DAAs, interferon-based therapy is becoming more infrequently used in Vietnam. However, data on the costs of interferon-based therapy are still essential for conducting accurate economic evaluations of DAA treatment, as interferon-based treatment will likely be the comparator . In June 2019, DAAs started to be covered by the national health insurance programme (NHI)parator  within t17, and a 2017 GDP per capita of US$236518. The seroprevalence of HCV in the general population has been estimated to be between 1 and 4.7%20, which is high relative to other countries in the region. In Vietnam, genotypes 1 and 6 predominate21. These genotypes are considered hardest to treat with interferon-based therapies and both genotypes 1 and 6 require prolonged treatment courses (48 weeks as opposed to 24 weeks)22.Vietnam is a lower-middle-income country in Southeast Asia with a population of over 95 million peopleThe Hospital for Tropical Diseases (HTD) in Ho Chi Minh City is the major referral hospital for infectious diseases in the south of Vietnam. Our cost estimation was performed in the context of the HTD in 2017.23. To enhance treatment efficacy, each of these injection-based treatments is combined with the antiviral tablet ribavirin  approved four interferon-based treatments within their first HCV treatment guidelines in 2013: IFN α-2a, IFN α-2b, Peg-IFN α-2a and Peg-IFN α-2bbavirin . In latebavirin . From th23. The dosage of Peg-IFN α-2b was calculated assuming an average body weight of 58 kilograms for men and 50 kilograms for women24.We estimated the quantity of the drugs required for an average treatment based on the recommended dosages within the 2013 HCV treatment guidelines from the MoH 23. The 23. These recommend that a patient should visit the outpatient clinic once prior to treatment, every four weeks during treatment and once after ending treatment. A summary of the required medical tests at these different stages of treatment is shown in23. Both of these regimens were considered in our analysis.The utilisation of the other resources and services  required to provide HCV treatment were based on the MoH 2013 treatment guidelinesOur cost analysis estimated the direct medical cost of HCV treatment from the health sector perspective . The dir25. One exception to this was the costs relating to the IFN drugs which were obtained from a 2017 report from the Drug Administration of Vietnam26.The identified resources and services  were cosThe main output was the total cost of the different treatments, stratified by the three main cost components: the cost of the drugs, the cost of the medical tests and the costs related to the clinical consultation fees.27.All costs were converted to US dollars (US$) following the average 2017 exchange rate where 22,370 Vietnamese dong (VND) equal 1 US$The total cost of the IFN treatment regimen was estimated to range between US$1,120 and US$1,962 and the total cost of the Peg-IFN treatment regimen between US$2,156 and US$5,887 . The cosWe estimated the costs of the three main components of HCV treatment: the drugs, medical tests and clinical consultation fees. The costs of the drugs contributed between 54–89% to the total treatment cost and were much higher for the Peg-IFN regimen. These were shown as a range because the exact price varies depending on which brand is used . This vaThe costs of the medical tests were also notable (US$498 for treating genotypes 2/3 and US$613 for treating genotypes 1/4/6) . The HCV28. The drug-related costs contributed the most (54–89%) to the total treatment cost  require a prolonged (48 weeks) duration of therapynt cost . The druThe results relate to the cost of a treatment regimen and not the cost per patient cured. Although the cost of treatment with IFN is cheaper, it is less likely to cure the patient successfully and the costs associated with treatment failure can be significant. Consequently, IFN treatment is rarely used in Vietnam.30, which is similar to our finding. Another study reported that in China31, the Peg IFN-2a and ribavirin for treating HCV genotype 1, cost US$174 per week (2016 prices), almost double our estimate.Studies in neighboring countries have reported the cost of Peg-IFN using the same doses. One study from Thailand reported that the Peg IFN-2a/2b and ribavirin for treating HCV genotypes 1/6 cost US$90 per week (2013 prices)These cost estimates relate to a standard treatment (based on MoH guidelines). It should be noted that in practice there will be variations in these treatment costs and resources utilized, such as for those not finishing the treatment regimen, experiencing treatment failure or those with co-infections such as HIV.32. However, even the patients covered by the NHI can incur significant out-of-pocket payments   recommend DAAs as the first-line therapyOur study has several limitations, for example, we focused on quantifying only the direct medical costs of HCV treatment. This includes the costs covered by the insurance system and the patient’s co-payment . However30. It is important that further HCV treatment costing studies are conducted in other low- and middle-income countries, particularly relating to the use of DAAs.Our analysis was performed in the context of the HTD in Ho Chi Minh City, which is a large hospital specialising in infectious disease. Whilst it is possible that there may be some minor variations in costs in other provinces in Vietnam, as the costs of both healthcare services and drugs are regulated centrally by the NHI department and MoH, our cost estimates are likely to be robust. Although the precise results and cost estimates of our study are not directly generalizable to other countries, they are consistent with reports from neighbouring countries, such as ThailandThe cost estimates were predominantly based on the price lists from HTD relating to 2017. However, it is possible that the costs, particularly those relating to the drugs, will vary over time.We have focused on conducting a costing study, hence further evaluation regarding the cost-effectiveness of the different treatments is required.46.A deeper understanding of the costs of the different treatment options is vital for supporting HCV policy decisions. Currently, there are few costing studies and economic evaluations of HCV treatment in low- and middle-income countriesWe found that treating HCV with IFN or Peg-IFN results in significant direct medical costs. We estimated that a 48-week Peg-IFN treatment regimen costs between US$3,956–5,887 in Vietnam. The majority of this figure relates to the cost of the drugs.Although the role of interferon-based therapy is diminishing, this cost data provides a foundation for evaluating the economic benefits and cost-effectiveness of switching to using DAAs.12.Of concern, we found that even patients receiving the maximum level of support from the NHI incur substantial out-of-pocket costs for their HCV treatment . ConsequAll data underlying the results are available as part of the article and no additional source data are required. In summary, the research can be considered a critical previous step towards improving access to DAAs in Vietnam. It was concluded that treating HCV with IFN or Peg-IFN results in high direct medical costs. DAAs are subsidised by the local National health insurance programme from June 2019. Some discretionary suggestions to improve the paper´s quality are listed below: It would be useful to have a supplemental spreadsheet that could be used as a parameter for further economic evaluations; this spreadsheet could have citations (or weblinks to the sources used) to allow quick update and checking by future researchers. An update regarding the actual use of IFN-based regimens for Hepatitis C treatment in Vietnam would be useful.1; this could bring additional savings if associated with the use of effective generic drugs2. Authors’ could also discuss, as another potential advantage of DAAs, the possibility of decentralising Hepatitis C treatment to primary health careIs the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Public Health; Health Technology Assessment; EpidemiologyI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. In summary, the research can be considered a critical previous step towards improving access to DAAs in Vietnam. It was concluded that treating HCV with IFN or Peg-IFN results in high direct medical costs. DAAs are subsidised by the local National health insurance programme from June 2019.Some discretionary suggestions to improve the paper´s quality are listed below:It would be useful to have a supplemental spreadsheet that could be used as a parameter for further economic evaluations; this spreadsheet could have citations (or weblinks to the sources used) to allow quick update and checking by future researchers.Response: We have included the full detail of the costs used within the analysis within Table 4.An update regarding the actual use of IFN-based regimens for Hepatitis C treatment in Vietnam would be useful.Response: We have added the following into the introduction.“We conducted a detailed analysis of the costs of treating chronic HCV with the pre-existing standard of care in Vietnam, IFN and Peg-IFN therapy. Since 2016, Vietnam has started to move away from interferon-based therapy towards DAA treatment regimens (in keeping with WHO guidelines). In June32. Consequently, due to its side effect profile and the increasing availability of DAAs, interferon-based therapy is becoming more infrequently used in Vietnam.  However, data on the costs of interferon-based therapy are still essential for conducting accurate economic evaluations of DAA treatment, as interferon-based treatment will likely be the comparator  within the analysis.”Unfortunately, there is currently no data on the exact numbers receiving interferon-based therapy nationally.1; this could bring additional savings if associated with the use of effective generic drugs2.Authors’ could also discuss, as another potential advantage of DAAs, the possibility of decentralising Hepatitis C treatment to primary health care Response: We agree and really appreciate your suggestion. We have added the following with your suggested references:“A further potential advantage of DAAs is that they may allow the possibility of decentralising hepatitis C treatment to primary health care facilities in some settings [3], which could also bring additional cost savings [4]. This benefit will depend on the local health system and needs further investigation.” This article presents important information on the cost of treatment for Hepatitis C virus with the older drug regimens that have been in use since 1991 (IFN and Peg-IFN). Although new recommendations are to use direct acting antiviral (DAA) treatments when available, it is important to understand the baseline or previous cost of treatment to accurately estimate the impact of transitioning to new treatment regimens.The results include a range of uncertainty in the cost of the drugs, based on different brands available, but there is no uncertainty or variation included in the cost of the tests or in the number of tests received per patient. Perhaps comment on whether all patients are expected to receive the same tests or if some will fail to complete treatment.The total cost per week and cost per month are referred to in the discussion, it would be clearer if these estimates are included in the results so that the reader doesn't have to calculate it themselves.The point about catastrophic health expenditure is interesting, but made me wonder whether it means patients aren't able to access treatment at all rather than spending beyond their means. Would this change with DAA treatment? Is there any information available about access to healthcare and how this varies according to the distribution of income in the country?Furthermore, the change to DAA drugs may result in changes to the number of tests and consultations required due to fewer side effects, which may be worth mentioning.It is stated that there are few costing studies and economic evaluations of HCV treatment in LMIC, but no references are included in the discussion to show the few that are available. Some are referenced earlier in the paper regarding IFN treatment, and there are published papers of economic evaluation of DAAs in Egypt and India (plus others in press). Figure 2 - I think some text is needed to explain this figure as I couldn't follow it. Do the uses of the words "co-payment" vs "out-of-pocket payment" here match the definitions in Box 1? Perhaps converting this into a box instead of a figure would allow for additional explanation of how the co-payment mechanism works? In addition, it wasn't clear to me how the co-payment applies to non-drug costs, and this will also apply to the discussion of catastrophic health expenditures.  There are a few points it would be helpful to address in the discussion: Introduction first paragraph contains an extra close brackets at the end of line 7.Methods first paragraph refers to gross per capita income but cites a source of GDP per capita. Clarify if referring to GDP, GNI, or per capita income which is referred to in discussion with a different source cited.Table 3 footnote refers to itself, should this refer to Table 4?Table 4, please indicate which class of drugs each brand name refers to so that it can be cross-referenced with Table 3.Figure 3 caption refers to itself, should this refer to Figure 2?press release on what price they pay may be helpful.The reference for the cost of DAAs is fairly old, unfortunately there is not much published on this but MSF'sDiscussion states that cost data related to IFN supports economic case to increase access to DAAs. Perhaps rephrase to indicate that the cost data provides a foundation for evaluating the economic case to treat with DAAs, as the case for use of DAAs is not made in this paper. Or remove as this is stated later in discussion as well (bottom of page 9 column 1). Minor changes including editorial points:Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?Not applicableAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Evaluation of health interventions in low and middle income countries, particularly related to the impact and cost-effectiveness of scaling up treatment for Hepatitis C virus.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This article presents important information on the cost of treatment for Hepatitis C virus with the older drug regimens that have been in use since 1991 (IFN and Peg-IFN). Although new recommendations are to use direct acting antiviral (DAA) treatments when available, it is important to understand the baseline or previous cost of treatment to accurately estimate the impact of transitioning to new treatment regimens. There are a few points it would be helpful to address in the discussion:  The results include a range of uncertainty in the cost of the drugs, based on different brands available, but there is no uncertainty or variation included in the cost of the tests or in the number of tests received per patient. Perhaps comment on whether all patients are expected to receive the same tests or if some will fail to complete treatment.Response: The costs were calculated in relation to a standard treatment (based on the treatment guidelines). There will be some variation and we have added the following to the discussion. “These cost estimates relate to a standard treatment (based on MoH guidelines). It should be noted that in practice there will be variations in these treatment costs and resources utilized, such as for those not finishing the treatment regimen. experiencing treatment failure or those with co-infections such as HIV.” The total cost per week and cost per month are referred to in the discussion, it would be clearer if these estimates are included in the results so that the reader doesn't have to calculate it themselves.Response:  We agree that this would be clearer and have added a column for the average cost per week for the drug cost in Table 3. The point about catastrophic health expenditure is interesting, but made me wonder whether it means patients aren't able to access treatment at all rather than spending beyond their means. Would this change with DAA treatment? Is there any information available about access to healthcare and how this varies according to the distribution of income in the country?Response: This is a very good point. We have added more in the text that the high costs may have meant that many patients were not accessing treatment, as well as leading to catastrophic health expenditure. Unfortunately, there is currently no information available about access to healthcare and how this varies according to the distribution of income in the country and we are planning to explore how it may change with DAA treatment in future work.“In Vietnam, the average income in 2016 was US$136 per month 34 . In comparison, the estimated costs of HCV treatment with IFN or Pre-IFN ranged between US$200 and US$480 per month ( Table 3). Given that even patients receiving the maximum level of support from the national health insurance programme incur substantial out-of-pocket payments for these treatments , it is likely that many patients will have been unable to afford interferon-based HCV treatment. This financial barrier may have led to many patients not being able to access treatment, as well as what is known as “catastrophic health expenditures” ( Box 1) )  35 . A variety of different thresholds are used to define this, such as 25% of total household expenditure/income or 40% of a household’s non-subsistence expenditure 35, 36 . Regardless of the exact threshold used, our results indicate that interferon-based treatments were causing catastrophic health expenditures in Vietnam. The importance of reducing such financial barriers is recognised in the Sustainable Development Goals” Furthermore, the change to DAA drugs may result in changes to the number of tests and consultations required due to fewer side effects, which may be worth mentioning.Response: We have the added the following in the “The move towards using DAAs” section“The new DAA drugs are ‘pangenotypic’, meaning they are similarly efficacious for different genotypes, removing the need for expensive genotype testing in specialist labs or prolongation of therapy for the predominant strains in Vietnam. Because DAA treatment regimens are shorter, with fewer side effects, there will also be cost savings associated with the reduced medical monitoring and consultations required during treatment compared to interferon-based therapy.”                It is stated that there are few costing studies and economic evaluations of HCV treatment in LMIC, but no references are included in the discussion to show the few that are available. Some are referenced earlier in the paper regarding IFN treatment, and there are published papers of economic evaluation of DAAs in Egypt and India (plus others in press).Response: We have added appropriate references for this statement – including two systematic reviews. “Currently, there are few costing studies and economic evaluations of HCV treatment in low- and middle-income countries [REFS 1-3]”REF 1: Chhatwal J, He T, Lopez-Olivo MA. Systematic review of modelling approaches for the cost effectiveness of hepatitis C treatment with direct-acting antivirals. Pharmacoeconomics. 2016;34(6):551-67.REF 2: He T, Lopez‐Olivo M, Hur C, Chhatwal J. Systematic review: cost‐effectiveness of direct‐acting antivirals for treatment of hepatitis C genotypes 2‐6. Alimentary pharmacology & therapeutics. 2017;46(8):711-21.REF 3: Chaillon A, Mehta SR, Hoenigl M, Solomon SS, Vickerman P, Hickman M, et al. Cost-effectiveness and budgetary impact of HCV treatment with direct-acting antivirals in India including the risk of reinfection. PloS one. 2019;14(6):e0217964. Figure 2 - I think some text is needed to explain this figure as I couldn't follow it. Do the uses of the words "co-payment" vs "out-of-pocket payment" here match the definitions in Box 1? Perhaps converting this into a box instead of a figure would allow for additional explanation of how the co-payment mechanism works? In addition, it wasn't clear to me how the co-payment applies to non-drug costs, and this will also apply to the discussion of catastrophic health expenditures. Response: We have changed Figure 2 to make it clearer and add more explanation of how the co-payment mechanism works within the text.31. However, even the patients covered by the NHI can incur significant out-of-pocket payments (Box 1) for HCV treatment. For the drug costs relating to HCV treatment, the patient’s out-of-pocket payment will be based on the price of the drug and the patient's co-payment rate (the proportion of the billed costs that insured patients pay) (Equation 1).“In Vietnam, the proportion of the population covered by the national health insurance programme (NHI) as of December 2016 is estimated to be 81.7%Equation 1: Out-of-pocket payment for the drugs = Price of the drug × Patient’s co-payment rate The patient’s co-payment rate is what is remaining after subtracting the proportion covered by the NHI (Equation 2). In the case of these drug costs, the proportion covered by the NHI (Equation 3) is given by three components . These are outlined in Figure 2.Equation 2: Patients co-payment rate = 1 – proportion covered by the NHI Equation 3: Proportion covered by the NHI = Drug related rate × Group related rate × Referral related rate 33 . The payment mechanism within the NHI is the same for the non-drug costs, but the drug related rates are superseded by the relevant non-drug rates (see equation 3).” Based on these rates, even with the maximum level of insurance cover, patients still have to pay 50% of the cost of the IFN drugs and 70% of the cost of the Peg-IFN drugs  32 . Furthermore, if patients attend the HTD without a formal referral from their primary health care facility, they have to pay for the full cost of the treatment (as though uninsured)  The co-payment mechanism of the non-drug costs is the same but with different rates. We used the drug cost as an example to show the general idea of how national health insurance works. We have made this clearer in the text. Minor changes including editorial points: Introduction first paragraph contains an extra close brackets at the end of line 7.Response: We have deleted the blanket. Methods first paragraph refers to gross per capita income but cites a source of GDP per capita. Clarify if referring to GDP, GNI, or per capita income which is referred to in discussion with a different source cited.Response: We have fixed the references for this and changed the values to GDP per capita. Table 3 footnote refers to itself, should this refer to Table 4?Response: We have fixed this (changing Table 3 to Table 4). Table 4, please indicate which class of drugs each brand name refers to so that it can be cross-referenced with Table 3.Response: We have fixed by adding subcategory for column 1 within Table 4. Figure 3 caption refers to itself, should this refer to Figure 2?Response: We have fixed this .press release on what price they pay may be helpful. The reference for the cost of DAAs is fairly old, unfortunately there is not much published on this but MSF's Response: We have updated the references related to the cost of DAAs“It has been estimated that widespread access to combinations of HCV DAAs is feasible, with potential target prices approximately US$50–$250 per person for a standard 12-week treatment course, significantly cheaper than the longer treatment regimens with IFN and Peg-IFN [REF 1-2]”REF 1: Hafez TA. Public Health and Economic Burden of Hepatitis C Infection in Developing Countries.  Hepatitis C in Developing Countries: Elsevier; 2018. p. 25-32.REF 2: Barber MJ, Gotham D, Khwairakpam G, Hill A. Price of a hepatitis C cure: cost of production and current prices for direct-acting antivirals in 50 countries. Journal of Virus Eradication. 2020. Discussion states that cost data related to IFN supports economic case to increase access to DAAs. Perhaps rephrase to indicate that the cost data provides a foundation for evaluating the economic case to treat with DAAs, as the case for use of DAAs is not made in this paper. Or remove as this is stated later in discussion as well (bottom of page 9 column 1).Response: Thank you for this suggestion. We have rephrased the statements in the discussion and conclusion.“This cost data related to interferon-based therapy indicates that switching to generic DAAs may lead to potential cost savings”“Although the role of interferon-based therapy is diminishing, this cost data provides a foundation for evaluating the economic benefits and cost-effectiveness of switching to DAAs.”


There is a pressing need for evidence-based scrutiny of plans to re-open childcare centres during the COVID-19 pandemic. Here we developed an agent-based model of SARS-CoV-2 transmission within a childcare centre and households. Scenarios varied the student-to-educator ratio , family clustering (siblings together versus random assignment) and time spent in class. We also evaluated a primary school setting , including cohorts that alternate weekly. In the childcare centre setting, grouping siblings significantly reduced outbreak size and student-days lost. We identify an intensification cascade specific to classroom outbreaks of respiratory viruses with presymptomatic infection. In both childcare and primary school settings, each doubling of class size from 8 to 15 to 30 more than doubled the outbreak size and student-days lost (increases by factors of 2–5, depending on the scenario. Proposals for childcare and primary school reopening could be enhanced for safety by switching to smaller class sizes and grouping siblings. Whether arguments are centred on human capital  or the economy , the conclusion is largely the same: childcare centres are re-opening (at least in some capacity) and this is taking place before a vaccine or herd immunity can mitigate the potential spread of SARS-CoV-2 (the virus that causes COVID-19). Outbreaks of COVID-19 in emergency childcare centres and schools have already been observed5, causing great concern as governments struggle to balance “flattening the curve” and preventing second waves with other pandemic-related sequelae such as the mental well-being of children and families, access to education and economic disruption.As nations around the world grapple with the psychosocial, civic and economic ramifications of social distancing guidelines6. However, these guidelines, which will result in significantly altered operational configurations of childcare centres and substantial cost increases, have yet to be rigorously examined. Moreover, discussions of childcare are presently eclipsed by general discussion of school reopening7 and the harms versus benefits of school closure during a pandemic9. That being said, for many parents, the viability of the school-day emerges from before- and after-school programming that ensures adequate coverage throughout parents’ work schedules. Yet, reopening plans often fail to mention the critical interplay between school and childcare, even though many childcare centres operate within local schools10. Consequently, a model that comprehensively examines the multifaceted considerations surrounding childcare operations may help inform policy and planning. As such, the purpose of the present investigation is to develop an agent-based model that explores and elucidates the multiple interacting factors that could impact potential SARS-CoV-2 spread in school-based childcare centres.Governments and childcare providers are tirelessly planning the operations of centres, with great efforts to follow public health guidelines for reducing SARS-CoV-2 contagion11. Additionally, all centres had to come up with a plan for daily screening of incoming persons, thorough cleaning of rooms before and during operations, removal of toys that pose risk of spreading germs, allowing only essential visitors, physical distancing at pick-up and drop-off, and a contingency plan for response should anyone be exposed to the virus . Further school-specific recommendations have been recently outlined by The Toronto Hospital for Sick Children10, which include specific guidelines for screening, hand hygiene, physical distancing, cleaning, ventilation, and masking. While this influential report has become the guiding framework for school reopening in Ontario, there remains no discussion of childcare operations in relation to SARS-CoV-2 spread. Guidelines for primary schools call for either full re-opening with up to 30 students per classroom attending every day, or with cohorts of 15 students attending in alternate weeks. Most recently and at the time of resubmission of this paper, Ontario has reported COVID-19 test positivity rates in schoolchildren that are twice that of other ages  to a maximum of 10 individuals 14. Modelling is used to determine how quickly the pathogen can spread15, how easily it may be contained16, the relative effectiveness of different containment strategies18, the social and economic impacts of lockdown2, and the role of schools in transmission20. Sensitivity analysis is crucial to assess whether model predictions are robust to uncertainties in data21, which is particularly important during a pandemic caused by a novel emerging pathogen like SARS-CoV-2. Agent-based models are particularly well-suited to situations where a highly granular description of the population is desirable and where random effects (stochasticity) are important. Such modelling has been used in both pandemic and non-pandemic contexts24, and is the basis of our methodology in the present work focusing on SARS-CoV-2 transmission in schools and households. Our objective is to use agent-based modelling to project the impact of student-educator  ratios and sibling grouping strategies on outbreaks of COVID-19 and student-days lost to classroom closure in a hypothetical childcare centre and primary school.Simulation models of infectious disease spread have been widely applied during the COVID-19 pandemic, as in previous pandemicsRA) or by grouping siblings (or otherwise cohabiting students) together (ST) in an attempt to reduce SARS-CoV-2 transmission. For the primary school setting, we considered student-educator ratios of 8:1, 15:1 and 30:1 with all students randomly assigned. For the 8:1 and 15:1 ratios, we also considered scenarios where cohorts of 8 or 15 students attend the same classroom in alternate weeks, labelled 8(A):1 and 15(A):1 respectively. In the primary school setting, we considered the higher student-educator ratio 30:1 as an example of larger class size. Some plans considered in reopening Ontario educational institutions divides this larger class size into two alternating cohorts of 15 students each with a single shared educator; we also label this scenario 15(A):1. Rotation occurs each week, so that one cohort engages with online material while the other receives face-to-face instruction for 5 days, after which the cohorts exchange roles. The student-educator ratios 8:1 and 8(A):1 were also included for comparison to smaller class sizes. For primary schools we considered only the RA assignment.A detailed description of the model structure, assumptions and parameterisation appears in the “25. Individuals were also subject to a constant background risk of infection (S) individuals exposed to the virus via community spread or interaction with infectious individuals  become exposed (E), while previously exposed agents become presymptomatic (P) with probability I) with probability A) with probability SARS-CoV-2 can be transmitted in households, classrooms, or in common areas of the school, all of which were treated as instances of homogeneous mixing on account of evidence for aerosolized routes of transmissionmentclass2pt{minim26. However, the role of children in SARS-CoV-2 transmission is still debated, and existing epidemiological evidence is limited by lack of empirical studies in school settings, which have been closed for much of 2020. Other studies show that children shed a similar amount of virus to adults27. To account for this ambiguity, we used contact matrices drawn from populations under ‘business as usual’ circumstances as a proxy of what contact rates would look like under a full reopening of schools and workplaces28. To account for the use of safety measures within the school (and the compliance of children and teachers with best practices), we consider low and high transmission rate scenarios , different classroom assignment schemes and school day durations. Primary schools, on the other hand, feature larger class sizes , assignment at random and possible division of students into weekly alternating cohorts. The results of simulations with the primary school model are detailed in the “E) is P) and A) proportions of attendees at days 12 and 19 respectively. Meanwhile, peak mean exposure in scenario 7:3 ST occurs on day 2, with The time evolution of the outbreaks are illustrated in Supplementary Fig. P and I with RA assignment, and status E). In the low transmission case, there is a reversal in trend, with peak proportions increasing with decreasing number of exposed (E) and presymptomatic (P) students per class. There is no obvious relationship between peak days for infected (I) and asymptomatic (A) individuals in the high transmission case, neither for asymptomatic (A) individuals in the low transmission case.Supplementary Table 29. When there is pre-existing immunity (as we suppose here), we study the effective reproduction number 30. This is the expected relationship, not only because of pre-existing immunity, but also because the The basic reproduction number entclass1pt{minimaThere is little correlation between mean population size Fig. a, line, entclass1pt{minimaThis is further demonstrated by the bar charts of Fig. Each individual simulation ends when all classes are at full capacity and there are no active infections in the population; aside from community infection, this marks the momentary halt of SARS-CoV-2 spread. From this, we get a description of the duration of the first outbreak . Box plots in Fig. This is mirrored in the low transmission case as well. A possible explanation lies in the number of students per classroom. The child–child contact rate Eq.  is far hS) and recovered/removed (R) childcare centre attendees provides additional information on the course of the outbreak, since they represent the terminal states of the infection process in each individual by the end of the outbreak. Figure R) overtaking the number of never-infected attendees (status S) on day 34 in the case of high transmission  in the childcare centre are given in Fig. The primary school setting shows the same cascade of intensifying outbreaks and rapidly mounting student-days of closure as class sizes increase Fig. . This efect Fig. a, and sientclass1pt{minimaThere is little difference between numbers of missed student-days between the similar scenarios 8:1 and 8(A):1, as well as as 15:1 and 15(A):1  in both the childcare centre and primary school settings. Secondly, we introduce a reduced time scenario to the childcare centre setting, representing a case where the school-day is shortened to decrease child–child contact in the classroom. Finally, we investigate the effect of varying other model parameters.Our examinations of both the childcare centre and primary school settings featured scenarios in which class sizes varied widely; here we isolate the effect of adding a single child or educator/teacher to each classroom in the institution. Supplementary Fig. We conduct a similar analysis in the primary school setting, where all classrooms have a single teacher and all classroom assignments in the school Bare random. In both low and high transmission scenarios, students can either attend class for all available school days (‘Constant Attendance’), or they can be organised into weekly-rotating cohorts (‘Alternating Cohorts’). In Supplementary Fig. Given the dependence of infection transmission probability on factors such as the rates of contact between children (and adults), family clustering, classroom size and class time, one potential avenue of risk reduction in both the childcare centre and primary school settings is the reduction of the time that students spend in class. Eq. Supplementary Fig. We conducted a sensitivity analysis on 10, public health agencies31, and public petitions32 have called for smaller class sizes, governments appear to be following some recommendations in reopening plans while not following others.We developed and simulated an agent-based model of SARS-CoV-2 transmission in childcare centre and primary school settings for the purposes of informing reopening policies. The model was configured to capture SARS-CoV-2 transmission in a local school building, since many childcare centres operate across several classrooms within schools. These services are an essential bridge for many parents who are unable to drop-off or pick-up children around school hours due to work. Our findings suggest that variability in class size  and class composition  influence the nature of SARS-CoV-2 transmission within the childcare context. Specifically, a 7:3 student-to-educator ratio that utilized sibling groupings yielded the lowest rates of transmission, while a 15:2 ratio consistently performed far worse. Findings for the primary school ratios show a similar acceleration of negative impacts with increasing class size. Findings from our simulations are sobering, as educators in the province lobbied for a 15 student cap on classrooms in Summer 2020. Our study suggests that classes of this size pose a tangible risk for COVID-19 outbreaks, and that lower ratios would better offset infection and school closures. While school reopening guidelines25.This accelerating effect of increasing classroom sizes occurs because of three factors working in concert. Firstly, a larger class means that a student is more likely to test positive for COVID-19 at some point. Secondly, when a larger class is closed as a result, it affects more students. Third, presymptomatic transmission and higher densities of students ensure that more children become infected before classroom closure is enacted, resulting in larger outbreak sizes due to more cases both before the closure, and after the closure as the infection continues to spread in households. This particular mechanism is specific to institutional outbreaks for infectious diseases with pre-symptomatic transmission worsened by aerosol transmission routes33. In Ontario, childcare classrooms were capped at a maximum of 10 occupants, overall (hence the 8:2 and 7:3 ratios in the present study)11. Conversely, procedures for traditional “school” classrooms have been given the go-ahead for 15 children (hence the 15:2 ratio). While allowable class sizes will differ somewhat as a function of child age and school location, it seems likely that early childhood and elementary school classes may actually surpass these numbers in Ontario. Our findings demonstrate that the 15:2 ratio represents a significantly higher risk, not only for SARS-CoV-2 spread, but for school closures. In one scenario (15:2 random assignment), the modeled outbreak lasted for 105 days. Given that childcare and schools are often operating within the same physical location, this policy discrepancy is questionable. Based on our simulations, a lower ratio (7:3) is indicated. Moreover, it appears that this configuration could be enhanced through the utilization of sibling groupings.Policies related to childcare and traditional school reopening have not been well integrated35. Given this, a proactive and preventative approach that builds in realistic levels of reduced class time would be better than a reactive strategy that yields unpredictable closure events due to outbreaks.An examination of student-days missed due to classroom closure further elucidates the favourability of smaller class size and sibling grouping as a preventative measure; again, this was observed in both high transmission and low transmission environments. In the most unfavorable scenario (15:2 RA), there were cumulatively 539 and 324 student-days missed in high versus low transmission settings, respectively. Conversely, in the best scenario , there were only 62 and 51 student-days missed. Thus, our simulations suggest that the lower ratios and sibling groupings offer a safeguard against high disruptive classroom closuresSeveral policy and procedural recommendations have emerged from this modeling exercise. First, it is recommended that childcare and school settings, alike, consider lowering student-to-educator ratios. Commensurate with the present findings, a 7:3 ratio  outperforms a 15:2 ratio on key metrics. Second, there also appears to be benefit associated with sibling groupings. Thus, a siblings together configuration should be considered. Third, the majority of transmission occurred in the classroom. As such, it is important for reopening plans to consider social distancing and hygiene procedures within classrooms - a recommendation that may only be feasible with fewer children in the classroom. It is unlikely that classrooms with 15 or more children will afford children with the necessary space to socially distance. Finally, in the primary school settings, significant benefits accrue for 15(A):1 relative to the 30:1 student-educator ratio, and thus decision-makers should reconsider the conventional model of putting 30 students in classrooms every day in favour of cohorts of 15 students alternating weekly. Implementing half-days in schools could also be considered.36.These results are also relevant for authorities facing the possibility of re-closing schools in light of an impending resurgence of COVID-19 due to a second or third pandemic wave. For instance, a combination of tamping down community transmission, in combination with restructuring schools according to some of these strategies  could enable schools to remain partially open during the resurgence, instead of needing to close them altogether37. However, multiple sources of bias must be considered, for instance on account of higher rates of asymptomatic transmission in children38. Due to asymptomatic transmission, outbreaks in schools may be harder to identify, and public health may classify adults in associated households as the index case of an outbreak, instead of asymptomatic children who brought the infection into the home. A systematic review of studies of the impact of school closure on COVID-19 transmission found that most studies identify an effect of closures, although a smaller number of studies less subject to biases find no effect39. Empirical validation of our model would entail analysis of outbreak sizes as they depend upon classroom size. This would require both accurate data on school outbreak sizes as well as knowing the class sizes in the affected school districts. This could be studied in future research.The impact of school closure on the transmission of COVID-19 is a widely studied topic40, the present study did not take these considerations into account. This present study also didn’t directly consider any difference in compliance between children of difference ages, though our consideration of low and high transmission scenarios represent differing levels of compliance with health regulations in both childcare centre and primary school contexts. Future simulation studies might consider how these social determinants intersect with childcare and school configurations. Also, the measures presented - decreasing class sizes, dividing large classes into smaller cohort alternating between in-class and online instruction, and limiting schooling to half-days - could be subjected to a cost-benefit analysis, where their effects on disease spread are weighed against any requisite impacts on learning, healthcare expenditure and the emotional well-being of students, teachers and parents. Additionally, we have not considered the effects of COVID-19 testing, since asymptomatic individuals are not prioritised in testing programmes, and many current health and safety policies simply ask whether the individual is experiencing any symptoms of COVID-19, upon which they are told to self-isolate. In the present model, classrooms are closed upon detection of a symptomatic case. This is representative of current reopening plans, so the effects of random COVID-19 testing of asymptomatic individuals was not treated here. Finally this study was primarily concerned with SARS-CoV-2 infection and student-days lost. That being said, there are many important outcomes to consider in relation to children’s developmental health in the pandemic. Longitudinal studies considering children’s learning and mental health outcomes in relation to new childcare and school configurations are strongly indicated41.Finally, the present study has a number of limitations that should be considered. While it is becoming increasingly clear that COVID-19 risk varies as a function of social determinants of health , along with opportunities for social distancingN households in the population, and a single educational institution  with M rooms and a maximum capacity dependent on the scenario being tested. Effective contacts between individuals occur within each household, as well as rooms and common areas  of the institution. All groups of individuals (households and rooms) in the model are assumed to be well-mixed.There are S), exposed to the disease (E), presymptomatic , symptomatically infected (I), asymptomatically infected (A) or removed/recovered (R), as shown in Fig. Each individual (agent) in the model is assigned an age, household, room in the childcare facility and an epidemiological status. Age is categorical, so that every individual is either considered a child (C) or an adult (A). Epidemiological status is divided into stages in the progression of the disease; agents can either be susceptible . Assignments are made such that there is only one educator per household and that children do not attend the same institution as a educator in the household (if there is one), and i will transmit the disease to a susceptible housemate with the age j with probability The basic unit of time of the model is a single day, over which each attendee (of the institution) spends time at both home and at the institution. The first interactions of each day are established within each household, where all members of the household interact with each other. An asymptomatically infectious individual of age i transmits the disease to some susceptible individual of age j with probability j will infect a susceptible individual of age i with probability The second set of interpersonal interactions occur within the institution. Individuals (both students and educators) in each room interact with each other, where an infectious individual of age To simulate community transmission , each susceptible attendee is infected with probability S) individuals exposed to the disease via community spread or interaction with infectious individuals  become exposed (E), while previously exposed agents become presymptomatic (P) with probability I) with probability A) with probability Figure The capacity of the sole educational institution in the model is divided evenly between 5 rooms, with class size and student-educator ratio governed by one of three basic scenarios: seven students and three educators per room (7 : 3), eight students and two educators per room (8 : 2), and fifteen students and two educators per room (15 : 2). Classroom assignments for children can be either randomized or grouped by household (siblings are put in the same class).I) are removed from the simulation after 1 day (status R) with probability A) remain infectious but are presumed able to maintain regular effective contact with other individuals in the population due to their lack of noticeable symptoms; they recover during this period (status R) with probability Symptomatically infected agents (I) agents depend on age and role. Individuals that become symptomatic maintain a regular schedule for 1 day following initial infection , after which they serve a mandatory 14-day isolation period at home during which they interaction with no one (including other members of their household). On the second day after the individual’s development of symptoms, their infection is considered a disease outbreak centred in their assigned room, triggering the closure of that room for 14 days. All individuals assigned to that room are sent home, where they self-isolate for 14 days due to presumed exposure to the disease. Symptomatically infected children are not replaced, and simply return to their assigned classroom upon recovery. At the time of classroom reopening, any symptomatic educator is replaced by a substitute for the duration of their recovery, upon which they reprise their previous role in the institution; the selection of a substitute is made under previous constraints on educator selection (one educator per household. with no one chosen from households hosting any children currently enrolled in the institution).The actions of symptomatic . Individuals are assigned to households as described in the “Upon population generation, each agent is initially susceptible (Households hosting educators are generated separately. As in the “R) to account for immunity caused by previous infection moving through the population. A single randomly chosen school attendee is chosen as a primary case and is made presymptomatic (P) to introduce a source of infection to the model. All simulations are run until there are no more potentially infectious  individuals left in the population and the institution is at full capacity. All results were averaged over 2000 trials.Initially, a proportion of all susceptible agents 28 was stratified into age categories of width 5 years starting at age 0 . The mean number of contacts per day Agents in the simulation were divided into two classes: “children” (ages 0–9) and “adults” ages 25–44). Available data on contact rates5–44. AvaP; all other members were marked as susceptible (disease status S). In each day of the simulation, each member of each household was allowed to interact with the infected member, becoming exposed to the disease with probability given in Eq. E. At the beginning of each subsequent day, presymptomatic individuals proceeded to infected statuses I and A, and infected agents were allowed to recover as dictated by Fig. For entclass1pt{minimaE) to progress to an infectious stage (I or A) since we were interested in finding out how many infections within the household would result from a single infected household member, as opposed to added secondary infections in later days. At the end of each trial, the specific probability of infection (D represents the total number of multiple occupancy households in the simulation. This modified disease simulation was run for 2000 trials each of different prospective values of We did not allow exposed agents (status Our model makes simplifying assumptions that may influence its predictions. For instance, we assume that classrooms are homogeneously mixing and did not take social structure into account. Social structure might slow the spread of COVID-19 in classrooms. We also assumed that public health authorities will respond to a confirmed case by closing the classroom, although in practice, they may keep the class running if they think the case does not represent an infection risk to children or adults. This would reduce the number of student-days lost to closure. Similarly, we did not account for potential contacts between school children outside of classes, although students of a classroom that has been closed may still interact with their classmates outside of school. Other simplifying assumptions are mentioned in the “Supplementary Information.


In some patients, migraine attacks are associated with symptoms of allodynia which can be localized  or generalized . Using functional neuroimaging and cutaneous thermal stimulation, we aimed to investigate the differences in brain activation of patients with episodic migraine (n = 19) based on their allodynic status defined by changes between ictal and interictal pain tolerance threshold for each subject at the time of imaging. In this prospective imaging study, differences were found in brain activity between the ictal and interictal visits in the brainstem/pons, thalamus, insula, cerebellum and cingulate cortex. Significant differences were also observed in the pattern of activation along the trigeminal pathway to noxious heat stimuli in no allodynia vs. generalized allodynia in the thalamus and the trigeminal nucleus but there were no activation differences in the trigeminal ganglion. The functional magnetic resonance imaging (fMRI) findings provide direct evidence for the view that in migraine patients who are allodynic during the ictal phase of their attacks, the spinal trigeminal nucleus and posterior thalamus become hyper-responsive (sensitized)–to the extent that they mediate cephalic and extracephalic allodynia, respectively. In addition, descending analgesic systems seem as “switched off” in generalized allodynia. During a migraine attack, most patients develop cutaneous allodynia, defined as pain perception evoked by normally non-noxious stimuli , 2. ThatThe associated manifestations of allodynia have clinical implications including 1) period of time for effective treatment in episodic migraine   period o, (2) difMost imaging research has been done between migraine attacks  , there aOur aim was to investigate brain activation in allodynic and non-allodynic migraine patients during their ictal vs. interictal state to assess cortical and subcortical differences underlying the phenomenon of migraine-associated allodynia as defined according to changes between ictal and interictal pain tolerance threshold in response to thermal stimuli using quantitative sensory testing (QST). We focused on two questions: (1) Are there any differences in response to noxious thermal stimulation in the migraine brain between ictal vs. interictal states along the trigeminovascular pathway using functional magnetic resonance imaging (fMRI)?; and (2) How are the brain response changes manifested in the generalized allodynic state different from those in the non-allodynic state? The observations and insights gathered from the brain changes in allodynia may help understand if the progression from no allodynia to generalized allodynia engages brain areas involved in the sensory, emotional and other aspects of migraine and how each is involved.http://ohsr.od.nih.gov/guidelines/helsinki.html) and the International Association for the Study of Pain. Subjects were recruited through participating physicians and online advertisements. After a telephone interview, participants were scheduled for a screening session during which all aspects of the study were described . To ensure compliance with the inclusion and exclusion criteria prior to subject enrollment, a study physician performed a full medical examination, and a detailed medical history was taken from the patients . Written informed consent was received from all participants by the study staff after answering any study-related questions.Subject recruitment and the experiment protocol were approved by the McLean Hospital Institutional Review Board and met the scientific and ethical guidelines for human pain research of the Helsinki Accord (The inclusion criteria were as follows: (i) episodic migraine as defined by the International Classification for Headache Disorders (ICHD-2) ; (ii) BeThe study consisted of two visits, one during the interictal period (baseline scan) and one during an ictal event (migraine scan). The initial interictal visit was scheduled when the patients had been migraine free for 72 hours and did not have any symptoms or signs of developing a migraine attack. For the ictal visit, arrangements were made so that the research team was available between 6am to 8pm on weekdays and weekends to scan the patients within 2.5 to 5 hours of the migraine attack onset.In order to determine individual sensitivity and pain thresholds to thermal stimuli, each subject participated in QST prior to each scan session. Thermal pain thresholds were measured on the face and dorsum of the hand, and the side of the body was determined based on which side the pain is felt more often during a migraine attack. The same area on the back of the hand was tested for all patients. Participants received between 3–5 thermal stimuli and the average of these values +1˚C was the threshold temperature that the participant would receive during the scan.The experimental paradigm included two visits to the McLean Hospital Brain Imaging Center. The scans during both visits consisted of a series of anatomical scans followed by a functional imaging scan. For both functional scans, a painful heat stimulus (threshold +1°C) was applied to the hand. After the ictal scan, patients were allowed to take their pain medications.Patients rated their pain while lying in the MRI scanner during each functional scan using a rating dial. They were instructed to assess the pain intensity evoked from each stimulus using a visual analog scale .A Federal Drug Administration-approved Thermal Sensory Analyzer  was used to deliver a thermal stimulus through a probe that was adapted to rest on the hand. The probe is 1.6 x 1.6 cm, or about one-half the size of the thumb. For warm heat, stimuli were given at 41˚C on the hand . For3, matrix = 64 x 64, 74 volumes, 41 slices) was used to acquire the functional images. High resolution, T1-weighted structural data were also collected from each patient using a 3D MPRAGE pulse sequence .Imaging was performed in a 3.0 T Siemens  Trio scanner using a circularly polarized (CP) coil. A Gradient Echo (GE) echo planar imaging (EPI) sequence , version 4.1.9. The preprocessing steps included skull stripping using the Brain Extraction Tool (BET) with bias field correction and neck removal. The volumes were motion corrected using FMRIB's Linear Image Registration Tool (MCFLIRT) and B0 unwarping was performed using FMRIB's Utility for Geometrically Unwarping EPIs (FUGUE) to correct for some field inhomogeneities. The data were spatially smoothed with a Gaussian kernel of 5 mm full width at half maximum (FWHM) and a high-pass temporal filter with cutoff of 60s was applied. First-level analysis on functional imaging data for each subject was carried out using FMRI Expert Analysis Tool (FEAT) Version 5.98. The recorded temperature traces for each participant were entered as the explanatory variables (EVs) for heat stimuli. EVs were convolved with a gamma-variate hemodynamic response function. Functional volumes were spatially normalized to the Montreal Neurological Institute (MNI152) template for group analysis, and individual data of right-sided migraine patients (who were stimulated on the right side) were flipped along the y-axis so that they correspond with the patients with left-sided migraine. Thus, in the group results the left side is the ipsilateral stimulation side, while the right side is the contralateral stimulation side. Patients with no dominant migraine side were also stimulated on the left. Contrasts were defined for the non-noxious and noxious thermal stimuli for each subject, and in the group level analysis contrasts were generated to compare allodynic patients to non-allodynic patients, and to investigate patients during their ictal and interictal state. Higher level group contrast analysis was carried out to calculate the intragroup and intergroup comparison activation maps using FMRIB’s Local Analysis of Mixed Effects (FLAME1) [p < 0.05).Functional imaging data processing and analyses were carried out using FMRIB Software Library (FSL) ((FLAME1) . All sta(FLAME1)  which isIn addition to the whole-brain approach, two region of interest (ROI) analyses were conducted: (1) ROIs were determined for the trigeminal ganglion and trigeminal nucleus based upon previously implicated areas in the trigeminal nociceptive pathway –23, and Fig 1 shows the flowchart of patient inclusions in the study. From the 51 episodic migraine patients, 26 patients completed both scan visits for this study. However, six patients were excluded from the analysis due to the long time separation between the interictal scan and the scan obtained during the migraine attack (> 1 year). Twenty patients completed both visits within 9 months . One female subject was excluded later from the imaging analysis due to the concerns of residual effects of a beta-blocker. Nineteen episodic migraine patients  were included in the final imaging analysis. A detailed description of demographic and migraine attack characteristics is shown in Table 1. There were no significant differences between males and females in age and migraine characteristics, but females used more preventative medications than males. In addition, age, sex, migraine characteristics and medication history were not significantly different between the allodynia groups defined by QST testing (see below). All of the participants had migraine for at least more than four years and experienced five to six migraine attacks on average each month with a range of one to twelve migraine attacks per month.SD = 2.5). Since we were interested in assessing the differences in brain activation among migraine patients based on their allodynic status defined by changes between ictal and interictal pain tolerance threshold at the time of imaging, migraine scan was delayed relative to the time of onset for an average of 4 hours [SD = 19.9). During this time QST was performed to measure the pain thresholds from which the allodynic status was determined (see below). Patients were experiencing comparable levels of pain  to 10 (maximum imaginable pain)).Time elapsed between the first and second visit ranged from 1 month to 9 months with an average of 3 months . Subjects abstained from taking their migraine medications for one dosing interval prior to their interictal scan session. They also had to refrain from taking their medication on the day of their ictal visit until after the scan was completed. Medication did not change between the first and second visit.Subjects were on a wide range of medications, including over the counter medicines  and prescribed medications . Fig 2. Allodynia state was determined based on the changes in the pain tolerance thresholds (>3°C) between face and hand when stimulated by the heat [Pain tolerance thresholds were determined on the hand and the face for all of the patients during both interictal (baseline (B)) and ictal (migraine (M)) visits using QST. The results for the allodynia status are presented in the heat , 27, 28.t(18) = 1.84, p = 0.1). The VAS data were compared within the allodynia groups as well and no significant differences were found between the ictal vs. interictal VAS scores in the allodynic groups: no allodynia (Face: 6.6 (B) vs. 6.3 (M), Hand: 5.4 (B), vs. 7.1 (M)), localized allodynia (Face: 4.6 (B) vs. 6 (M), Hand: 4.9 (B) vs. 6(M)), generalized allodynia (Face: 7.34 (B) vs. 7.1 (M), Hand: 7.9 (B) vs. 7.2 (M)).The noxious heat stimulus (threshold +1°C) applied to the dorsum of the hand evoked on average a pain intensity of 6.1 ± 3 (SD) during the interictal scans and 7.4 ± 2.6 (SD) during the ictal scans on the 0–10 scale. In spite of the fact that participants were pain-free in the baseline (B) visit and experiencing head pain in the migraine (M) visit, there was no significant difference between the VAS ratings between the ictal vs. interictal visits  applied to the dorsum of the hand during the interictal and ictal scans are presented in S2A and S2B Tables in S1 File.Imaging results are presented in Ipsilateral activation in response to noxious heat stimulation was observed in the thalamus, middle cingulate, precentral, and superior frontal gyrus. Contralateral activation was found in the anterior insula, caudate, palladium, temporal pole, middle temporal, and postcentral gyrus. And bilateral activation was seen in response to stimulation in the supramarginal, inferior parietal, inferior operculum gyrus and cerebellum, although activation in the cerebellum was mainly contralateral.Ipsilateral activation in response to noxious heat stimulation was observed in the middle cingulate, precentral, and superior frontal gyrus. Contralateral activation was seen in the pons, anterior insula, caudate, palladium, temporal pole, middle temporal, and postcentral gyrus, as well as in the cerebellum. Bilateral activation was observed in thalamus, rolandic operculum in the occipital cortex, supramarginal, inferior parietal and inferior operculum gyrus.Fig 3 and the corresponding activations are shown in Table 2A and 2B. The main differences were significantly stronger ipsilateral activation during the migraine scan in the anterior and posterior insula, supramarginal gyrus and cerebellum, as well as stronger contralateral activation in the anterior and middle cingulate, trigeminal nucleus and brainstem (pons). Significantly stronger bilateral activation during the migraine attack was found in the occipital cortex, and posterior cingulate. There were also brain regions that showed increased activation during the interictal scan compared to the ictal scan. The main differences were in the frontal cortical regions and temporal regions. There was an increased activation in the ipsilateral precentral gyrus, postcentral gyrus, as well as putamen. Contralateral stronger responses were found in the inferior, superior and middle temporal gyrus.Contrast analysis results for brain activation in ictal vs. interictal scans in response to noxious heat (threshold +1°C) applied to the hand are shown in Fig 4. The main differences between the two groups were in the activation of the contralateral brainstem (pons), insula and thalamus, which were present only in the generalized allodynia group and not in the no allodynia group. On the other hand, the no allodynia group showed increased activity during a migraine attack in the posterior cingulate and periaqueductal gray (PAG) that was not observed in the generalized allodynia group.Additional analyses were performed to compare brain activation in ictal vs. interictal scans in response to noxious heat in patients who showed changes in pain threshold in both face and hand , and in the patients who showed no change in the pain thresholds between the two visits . The results are presented in Fig 5 ROI-based comparison results for % signal change between the interictal and ictal scans for noxious stimulation of the hand are shown. The activations are presented along the trigeminal nociceptive pathway in patients with generalzied vs. no allodynia for the left thalamus and left trigeminal nucleus, ipsilateral to the side of stimulation and for the trigeminal ganglion on the contralateral side. The results show a higher level of signal change, suggestive of an increased hypersensitivity, for generalized allodynia vs. no allodynia in the thalamus and the trigeminal nucleus. The level activity for the trigeminal ganglion was comparable between the two groups.In Fig 6 present % signal changes in ictal vs. interictal scans for thalamic sub-regions according to their cortical connectivity. For this analysis, thalamic segmentation was performed using a probabilistic atlas of sub-thalamic regions that were generated based on white-matter connectivity between the thalamus and cortical areas [The results in al areas , 26. TheWe designed a study to assess the brain activation in migraine patients in response to noxious thermal stimulation during both a migraine attack  and between attacks  in the context of the changes in the thermal pain tolerance threshold as an index of allodynia. Aside from the allodynic measures, there are a number of features that distinguish this study from others: 1) the migraine happened naturally and was not induced –32; (2)  the migrFig 2. Questions about experiencing allodynic symptoms were also asked before enrolling patients to ensure compliance with the inclusion criteria. QST is sometimes described as the gold standard for detecting whether a patient with migraine has allodynia at a particular time [Fig 1.Differences in thermal thresholds between ictal vs. interictal visits for migraine patients were used to categorized patients’ allodynic state which allowed defining three distinct groups of no-allodynia, localized allodynia, and generalized allodynia with distinct pain tolerance profiles as shown in lar time , 27, altlar time , 4, 9 anFig 3 and Table 2A and 2B we observed differences between these two states with increased activation to thermal stimuli in trigemino-thalamic pathways  and other brain regions . Activation in these regions to thermal stimuli was previously reported in interictal migraine patients by our group [As shown in ur group , 33–37 aur group –40. ThesOur major findings were the observed differences between the no and generalized allodynia groups including increased activations in ictal vs. interictal state of the contralateral brainstem (pons), insula and thalamus, which were observed only in the generalized allodynia group and not in the no allodynia group, and that the no allodynia group showed increased activation during a migraine attack in the posterior cingulate and periaqueductal gray (PAG) that was not observed in the generalized allodynia group.These findings suggest that in the no allodynia group, the PAG does what it supposes to do which is inserting inhibitory effects on ascending nociceptive neurons in spinal and trigeminal dorsal horn , 42. AllAs noted in the results, regions showing increased activation in ictal vs. interictal state outside the traditional trigemino-thalamic pathways included a number of cortical regions: the cingulate cortex, orbitofrontal regions, the anterior and posterior insula, the calcarine, and the supramarginal cortices. The cingulate displayed greater increases in the contrast for ictal vs. non-ictal state for the anterior (ACC), middle (MCC) and posterior (PCC). These regions reflect possible complex involvement in pain emotion  and otheThus, multiple cortical and subcortical regions display significantly increased responsivity to noxious heat during the ictal  state. A few findings contribute to these enhanced profiles. As noted in our prior report, cortical connectivity may also be involved in cortico-cortical connections noted for sensory areas in migraine  suggestiNumbers of subjects: Getting scans of migraine patients during their migraine attack is a real challenge. Although 51 patients were recruited to the study, and our data for ictal vs. interictal comparison were reasonable , the patient numbers for comparisons for the allodynic vs. non-allodynic states were small. However, our psychophysics measures helped “phenotyping” these subgroups. Considering that this was a prospective clinical imaging study, and the first visit was the interictal scan, it might be understandable that less participants came back to the ictal visit where brain activations were measured during the migraine headache. Since we were interested in the neural responses to noxious stimulation in the ictal vs. interictal states and how the changes manifest in the generalized allodynic state are different from those in the non-allodynic state, we could only focus on patients who completed both visits. Also, no healthy controls were included in the study. (2) Migraine cycle: Although all interictal scans were performed at least 72 hours after the last migraine attack and the patients did not have migraine during the baseline visit, their headaches were not monitored following the interictal scan. This information might have been useful for determining the specific phase of the migraine cycle. (3) Allodynic state: In patients who experience mild forms of allodynia, it is likely that the symptoms of allodynia may not always be present or experienced similarly with every single attack. As such, symptoms experienced on ‘average’ by a patient  and the QST-based determinations at a given time may not always align. (4) Order effects: There is an order effect due to subjects not being randomized between interictal and ictal-phase scan sessions which was not possible to avoid in this study. (5) Laterality: When the patients came for their ictal scan the stimulation was applied on the side that patients were feeling the most pain, or if it was equal on both sides it was applied to the left side. For all of the subjects consistently the sites were the same for both scans. However, since for the analysis the data from the right-sided migraine patients were flipped and analyzed together with the data from the left-sided migraine patients, it is difficult to make any inferences about the laterality effects of the migraine itself in the results. Flipping the brain images could be also a limitation because of the structural and functional differences between the right and left hemispheres [Medication: The issue of medication (noted in S1 Table in S1 File) used by the patients is always a confound in differentiating between the disease and medication effects on the brain. The patients were asked to refrain from taking any medications for 48 hours before their scan. In this study, most patients were on either triptans or non-steroidal anti-inflammatory drugs (NSAIDs) or no medication. However, since this was a paired-wise comparison and each subject served as his/her own control, at an individual subject level the residual effects of medications were canceled out in the analysis of differences between interictal and ictal scans.There are a number of caveats that are worth consideration: (1) ispheres . (6) MedAllodynia during a migraine attack is quite common and present in over 60% of patients. Based on the present findings, there are distinct patterns and activations in the no vs. generalized allodynia patients and a potential trigeminovascular pathway was detected that may facilitate the development of generalized allodynia. In particular, it seems that increased functional activity of the spinal trigeminal nucleus and posterior thalamus during an attack distinguishes patients who are allodynic vs. those who are not during their attacks. Furthermore, the thalamic subregion that connects to the temporal and prefrontal cortices shows higher activation during a migraine attack. Previous studies have demonstrated activation of the temporal pole during an attack and changes in plasticity of the temporal cortex in patients with high migraine frequency , 36.S1 File(DOCX)Click here for additional data file.


This cohort study examines the association between age at exposure to household dysfunction during childhood and adolescence and outcomes in early adulthood. Is age at exposure to negative experiences in childhood and adolescence associated with subsequent adverse outcomes?In this cohort study of data on 605 344 individuals aged 19 years from Denmark, exposure to negative experiences in early adolescence was more strongly associated with later adverse outcomes than was exposure in early childhood.The findings suggest that policy interventions targeting individuals exposed to negative experiences during childhood should focus on individuals exposed to negative experiences in adolescence. The current focus on the association of negative experiences in early childhood with adverse outcomes later in life is based on limited empirical evidence.To evaluate whether age at exposure to negative experiences in childhood and adolescence is associated with outcomes in early adulthood.This cohort study used population data from administrative sources for all Danish individuals born between 1987 and 1995 who were living in Denmark at 19 years of age. Data were analyzed in July 2020.Exposure to 6 household dysfunction items (HDIs) from birth to 17 years of age by age group. Age groups were as follows: 0 to 2 years (early childhood), 3 to 5 years (preschool), 6 to 12 years (mid-childhood), and 13 to 17 years (early adolescence). The 6 items were parents’ unemployment, incarceration, mental disorders, death, and divorce and the child’s foster care experiences.Mental disorders, low educational attainment, disconnection from education and the labor market, and criminal charges. A fixed-effects model was used to estimate the dose-response and age-specific associations between HDI exposure and the collated outcome measure.P < .001). Similarly, the risk of experiencing adverse outcomes varied significantly in association with age at exposure. Exposure during early adolescence was more strongly associated with adverse outcomes than was exposure during early childhood .The study sample included 605 344 individuals observed from birth to 19 years of age . Overall, 278 115 individuals (45.94%) were exposed to 1 or more of the 6 HDIs from birth to 17 years of age. Exposure was most prevalent at 1 year of age , and parental unemployment was the most common HDI (15.5% observed in mid-childhood). The risk of experiencing the 4 outcomes was monotonically associated with the number of HDIs. For example, experiencing 1 HDI between birth and 17 years of age was associated with an increased risk of experiencing an adverse outcome by approximately 1.0 percentage point (β = 0.011; 95% CI, 0.010-0.012; In this cohort study, exposure to negative experiences in early adolescence was more strongly associated with later adverse outcomes than was exposure at other points in childhood. Knowledge of age-specific associations is important information for policy makers who need to prioritize resources targeting disadvantaged children and youths. This third and last perspective on the dose-response association reflects the hypothesis that chronic or recurrent stress is associated with negative outcomes in physiological and psychological functioning . In summary, the literature has shown 3 perspectives on when exposure to positive or negative experiences may be associated with outcomes later in life: (1) the early childhood critical period, (2) the adolescent critical period, and the (3) dose-response association. Each perspective draws on equally plausible explanations of brain development and the consequences of stress; however, the empirical evidence in terms of their relative importance is scarce.Empirical evidence on age-specific effects of positive or negative experiences is not sufficient for use in building policies. Most of the existing evidence relies on small samples,The hypothesis of this study was that associations between exposure to negative experiences in childhood and later adverse outcomes vary by age at exposure. This study had 3 main objectives: (1) to assess the dose-response association between negative experiences during childhood and adolescence and outcomes later in life, (2) to examine the association between age at exposure to negative experiences and outcomes later in life, and (3) to examine the dose-response association by age at exposure.STROBE) guideline.This cohort study used prospective population data for all Danish individuals born from 1987 to 1995 who were living in Denmark at 19 years of age (N = 605 344). All Danish residents have a unique personal number that identifies their interactions with the public sector  and several private institutions  and that enables family linkages. Statistics Denmark collects information on these interactions by the start and ending dates (since 1980) and grants access to this administrative data for research purposes. Data were analyzed in July 2020. The study was approved through a long-standing agreement between the Rockwool Foundation Research Unit and Statistics Denmark. Data were deidentified, and informed consent was waived following the Danish Data Protection Law, article 14(5b). This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (19: (1) parental divorce, (2) prolonged unemployment (>9 months within a year) of 1 or both parents, (3) incarceration of the father, (4) inpatient treatment of a parent for mental illness, (5) foster care placement of the child, and (6) death of 1 or both parents  commonly recognized as factors associated with a range of later adverse outcomesWith this information, I constructed 3 different variables of HDI exposure. First, to assess the dose-response association between HDIs and later outcomes, I calculated the number of age-years of HDI exposure between birth and age 18 years for everyone in the sample. To account for dose, exposure to 2 different HDIs at a given age counted as exposure at 2 ages rather than just 1. Also, an HDI spanning multiple ages counted at each age that it affected.24Second, to assess the age-specific associations between HDI exposure and later outcomes, I constructed 4 binary variables that took the value 1 if the individual had been exposed to 1 or more HDIs in the following age groups: birth to 2 years, 3 to 5 years, 6 to 12 years, and 13 to 17 years. These age groups follow standard categories used in the literature and reflect knowledge of sensitive periods in brain formation.Third, to assess whether a dose-response association existed between HDI exposure and later outcomes within the 4 age groups, I constructed 4 count variables that measured duration of HDI exposure in years in the following age groups: birth to 2 years, 3 to 5 years, 6 to 12 years, and 13 to 17 years.25 All outcomes were measured at ages 18 and 19 years  for all analyses.I conducted 3 sensitivity analyses. First, I evaluated whether the age-specific associations reflect proximity in time between exposure and outcome. I constructed 10 binary outcome variables that equaled 1 if the individual experienced the adverse outcome at each of the 10 years between age 20 and 29 years . Parental divorce and child foster care had the weakest correlation .Of the 605 344 individuals in the study sample , 278 115 (45.94%) had been exposed to 1 or more of the 6 HDIs between birth and 18 years of age (eTable 1 in the The baseline mean (SD) risk for 4 adverse outcomes were as follows: being diagnosed with a mental disorder, 3.9% (17.9%); being charged with a criminal offense, 6.8% (25.2%); becoming disconnected from education and the labor market, 3.3% (17.9%); and not graduating from primary school, 2.0% (14.1%) (eTable 3 in the P < .001). Results were robust to a daily, rather than a yearly, definition of HDI exposure , and exposure in early adolescence was associated with an increased risk of 5.8 percentage points . Compared with the baseline risk of 13.4%, the risk of experiencing an adverse outcome increased 7.4% in association with early childhood exposure and 43.3% in association with adolescent exposure. Except for 1 case, the estimated coefficients were significantly different in the pairwise comparison of age groups (eTable 4 in the P < .001), but exposure to 7 HDIs was associated with an increased risk of 23.4 percentage points . However, fewer indications of a dose-response association were found within the other age groups.P < .001) compared with exposure in early childhood and outcomes at 20 years of age  (P < .001), where distance in time between exposure and when the outcome is measured is smallest for the second association (8-14 years vs 12-16 years). This finding suggests that proximity does not drive the age-specific pattern presented in The stronger association between HDI exposure in early adolescence and outcomes in early adulthood compared with HDI exposure in childhood may reflect time between exposure and when the outcome was observed. In this case, associations would decrease in size when the time between exposure and outcome was increased. I tested this theory by modeling the association between exposure in each of the 4 age groups and the risk of experiencing adverse outcomes, measured at each age from 20 years to 29 years. There was a stronger association between exposure in early adolescence and the outcome when measured at age 29 years  . A similF statistics of differences between coefficients), supporting the finding that exposure at this age differed from exposure at other ages. Few of the age-specific associations between HDI exposure and later adverse outcomes differed between subsamples, suggesting that the age-specific associations between HDI exposure and later adverse outcomes did not vary by maternal age.Parents’ age confounds child’s age, and the age-specific associations between the HDIs and the adverse outcomes may also reflect variation in parental problems by parental age. I analyzed whether the age-specific associations found in 11 Exposure to incarceration of the father , mental illness treatment , and parental divorce in early childhood was associated with adverse outcomes . Furthermore, exposure to foster care , incarceration of the father , and mental illness treatment  in early adolescence was associated with adverse outcomes. In addition, exposure to parental unemployment , incarceration , mental illness treatment , and parental death  in mid-childhood was associated with adverse outcomes. The estimated coefficients are shown in eTable 6 in the P < .001] vs β = 0.005 ). The estimated coefficient of exposure during early adolescence was significantly different from the other coefficients   are more vital for later outcomes than the activities disrupted during early childhood. Second, the age-specific associations did not seem to reflect proximity in time between exposure and the outcome measure. Third, not all HDIs had significant associations with outcomes overall or within each age group; foster care in particular was associated with later adverse outcomes.These insights have several implications. First, the age-specific associations between HDIs and later outcomes resonate with anecdotal evidence about exposure to negative experiences, but my study is among the first to enrich this evidence with data that are sufficient to show reliable patterns at the population level. The results presented here represent information for decision-makers seeking to optimize societies’ scarce resources by targeting disadvantaged groups at the right time.7 described above, which promotes adolescence as a second window of opportunity for development of appropriate interventions. If individuals are particularly susceptible to negative influences during early adolescence, they may also be likely to be susceptible to positive influences. This knowledge is helpful for understanding the potential for positive developments among adolescents, even among those with heavy problem loads.Second, the association between exposure in adolescence and adverse outcomes resonates with the UNICEF initiative10 The literature has mainly focused on abuse and neglect, which are often the main reasons for placing a child in foster care. However, from a policy perspective, being able to link these 2 subjective concepts (abuse and neglect) that may be difficult to observe in a child to a tangible system may provide useful information regarding which individuals to target with interventions.Third, the finding that foster care was among the HDIs with the strongest association with adverse outcomes may not be surprising given the existing literature on adverse childhood experiences.This study has limitations. First, the results reflect a single geographic location and a specific historical period. Denmark was a useful setting because of the country’s generous welfare state, which may ameliorate the consequences of HDIs, and findings from Denmark suggest that there may be stronger associations and larger differences between age-specific exposure than in countries in which consequences of HDIs are not likely to be ameliorated. In particular, the small association found between HDI exposure in early childhood and adverse outcomes may reflect the welfare services provided in Denmark during the first years of life, which are specifically meant to equalize opportunities for growth and development among children. The findings presented here may therefore represent a lower-bound estimate of the associations. Still, replication in other contexts is needed to gain a deeper understanding of age-specific associations of HDIs. Second, although the administrative data provide precise measures of HDI exposure, their objective character reveals little about how an individual experiences the exposure. For example, in the analyses, I define parents’ hospitalization for treatment of mental illness as an HDI; however, in a family in which a parent experiences mental illness, a problem that may be correlated with poor parenting skills, the hospitalization may represent a positive break from stressful parent-child interactions. The actual consequences of this HDI may therefore be the opposite of what I expected.In this cohort study, youth age at exposure to 1 or more HDIs was associated with outcomes in early adulthood. Exposure during early adolescence was more strongly associated with the risk of experiencing an adverse outcome compared with earlier points in childhood. The results of the study also suggest a dose-response association between HDIs and later adverse outcomes, yet this finding seems to be most pronounced in early adolescence. An association of proximity between exposure and the time at which the outcome was measured did not influence the overall results. In contrast, foster care was one of the HDIs with the strongest association with adverse outcomes, but the exclusion of this item did not undermine the results.