ArticlePDF Available

Social inequality – a forgotten forgotten factor in pandemic influenza preparedness.

DOI:10.4045/tidsskr.17.0273
Authors:
Svenn-Erik Mamelund at OsloMet - Oslo Metropolitan University
Svenn-Erik Mamelund
  • OsloMet - Oslo Metropolitan University
Download full-text PDF
Read full-text
Download citation

Abstract

Reducing social inequality in health is at the core of international health work, but does not form part of the discussionon international preparedness plans for pandemic influenza. This is surprising given that influenza pandemic mortality rates are highest among those with the lowest socioeconomic status. This is not conducive to achieving the international goals of reducing social inequality in health and ensuring good health for all by 2030.
Content uploaded by Svenn-Erik Mamelund
Author content
All content in this area was uploaded by Svenn-Erik Mamelund on Jun 28, 2017
Content may be subject to copyright.
28.6.2017 | Social inequality – a forgotten factor in pandemic influenza preparedness | Tidsskrift for Den norske legeforening
Social inequality – a forgotten factor in pandemic
influenza preparedness
GLOBAL HELSE
SVENN-ERIK MAMELUND
E-post: Svenn-Erik.Mamelund@afi.hioa.no
Svenn-Erik Mamelund (born 1969), PhD and research professor at the Work Research Institute, Oslo and Akershus University College
of Applied Sciences. He was previously employed at the Norwegian Institute of Public Health, and has conducted research on
historical influenza pandemics, with a particular focus on the Spanish influenza.
The author has complete the ICMJE form and reports no conflicts of interest.
Reducing social inequality in health is at the core of international health work, but does not form part of the discussion
on international preparedness plans for pandemic influenza. This is surprising given that influenza pandemic mortality
rates are highest among those with the lowest socioeconomic status. This is not conducive to achieving the
international goals of reducing social inequality in health and ensuring good health for all by 2030.
The World Bank’s latest ‘Global Crisis Response Platform’ report claims that the most serious threats to human life and
economic security are climate change, conflicts and pandemics (1). In recent years, several infectious diseases, such as
Middle East respiratory syndrome coronavirus (MERS-CoV), Zika and Ebola, have been characterized as pandemic
threats.
The Ebola epidemic in West Africa killed more than 11 000 people in the period 2014–15, and exposed failings in the
global epidemic preparedness. In response, the Coalition for Epidemic Preparedness Innovations (CEPI) was formed
recently (2). The aim is to produce vaccines, initially against the three aforementioned viruses, and then to conquer new
local epidemic outbreaks. During the launch of CEPI at the World Economic Forum in January 2017, the head of CEPI, Bill
Gates, argued that the pandemic threat with the greatest potential to harm society and the economy was a new
influenza pandemic (3).
The World Bank suggests that the annual cost of a new, less serious pandemic is USD 570 billion, which represents 0.7% of
the global gross domestic product (GDP). A serious pandemic like the Spanish influenza of 1918–19 can cost as much as
5% of the global GDP, or almost USD 4 trillion (1). The Spanish influenza killed 50–100 million people (4); 5–10 times more
than the number who perished during World War I.
Influenza pandemics past and present
Influenza pandemics have occurred 3–4 times every century since the 16th century, and have not been linked to
fluctuations in the economy or conflicts (5). In the last century, in addition to the Spanish influenza, we also had the
Asian influenza in the period 1957–58 and the Hong Kong influenza from 1968 to 1970. The last pandemic, in 2009–10,
killed 200 000 people globally (6). The number of pandemic-related deaths per 1 000 inhabitants has fallen over time:
1918–19 (27– 54), 1957–1958 (0.7), 1968–1970 (0.3) and 2009–10 (0.03) (4–6).
Who will be most at risk in a new influenza pandemic? A natural answer is young children, the elderly and people who
are already sick, as is the case during the annual influenza epidemics. During pandemics, people who are already ill are
vulnerable, but it is young adults who are affected the most (6–8). What about the socioeconomically disadvantaged?
During the Spanish influenza pandemic, mortality rates differed considerably between high and low-income countries
(9) and between the rich and the poor in towns with a large degree of social inequality. In Oslo, the highest mortality
rate was among the working classes, those living in small flats and people on the east side of the city (10). In Chicago, it
28.6.2017 | Social inequality – a forgotten factor in pandemic influenza preparedness | Tidsskrift for Den norske legeforening
was the illiterate, the unemployed and those with the most cramped living conditions who suffered the highest
mortality rates (11). During the 2009 pandemic, the mortality rate was 20 times higher in some South American
countries than in Europe (6), and three times higher in the poorer parts of England compared to the affluent parts (12).
There is not much we can do to reduce the likelihood of a new pandemic. However, we can draw on historical experience
to prevent social inequality in mortality rates during future pandemics.
Social inequality and global pandemic response plans
The European Union (EU), Norway, the World Health Organization (WHO) and the USA aim to reduce social inequality
in health in a generation (13–17). The World Bank, the EU and the Centers for Disease Control and Prevention in the USA
have adopted a ‘One Health’ strategy with a view to improving the preparedness for pandemic threats, with a particular
focus on lowincome countries (18–20). The strategy is a transdisciplinary approach for the early identification,
prevention and reduction of health threats to humans, animals and the environment. In addition to the aforementioned
CEPI, the World Bank also launched a pioneering funding scheme – the Pandemic Emergency Financing Facility (PEF) in
2016 – aimed at the rapid prevention of the spread of pandemic threats in low-income countries (21). These measures can
play an important role in the UN’s goal to eradicate poverty and ensure good health for all by 2030 (22).
In view of the international objectives of reducing social inequality in health and implementing measures to conquer
pandemic threats that arise in low-income countries, it is striking that international documents do not address the
question of how social disparities in mortality rates are to be reduced during the next influenza pandemic. This applies
to the preparedness plans by WHO, the USA, Canada, Australia, the EU and its 28 member countries, Iceland, Norway,
Switzerland, Turkey, Macedonia, policy documents by the World Bank, general sociodemographic projections, and
plans to reduce the impact of pandemics on indigenous populations (23–30). The complete absence of discussion on
social inequality in the pandemic response plan for England (12) has already been pointed out, but the failing in
international pandemic plans is something that is only now coming to light.
Internationally, the biomedical target groups for pandemic vaccines are health workers, high-risk age groups, pregnant
women and people with underlying diseases, while target groups defined on the basis of socioeconomic status are not
mentioned (23, 27, 29–31). However, indigenous populations are covered in pandemic plans for the USA, Canada and
Australia in the same way as the biomedical target groups (29–31).
It is unclear why those who devise plans do not discuss how to avoid social inequality in mortality rates in the event of a
new pandemic. Have the rich countries – who have prepared such plans – been most concerned about reducing social
inequality in diseases that take the most lives in rich parts of the world, such as cardiovascular disease and cancer? Has
this been at the expense of the interest in social inequality in infectious diseases that are rare or have little prestige, or
which have been eradicated or have a low mortality rate in our part of the world? Could it be that those who devise
pandemic plans consider influenza to be a disease which, beyond the biomedically defined risk groups, is random, and
therefore socially blind? Is that the reason why there is little emphasis on research showing that social conditions have a
bearing on who dies during a pandemic?
Need for transdisciplinary pandemic research and pandemic preparedness
plans
Although several studies have shown social inequalities in pandemic mortality rates both 100 years ago and in 2009 (6,
9–12), more studies are needed on the biological and social mechanisms that drive the inequality. These may relate to
poor nutritional status, concurrent illnesses, cramped living conditions and a lack of understanding of or access to
health advice/vaccination recommendations due to poor reading and writing skills. There is also a lack of studies that
can reveal whether the mortality rate for the socially disadvantaged was higher due to a greater incidence of influenza or
a higher mortality rate – or a combination of these.
The influenza models used in the pandemic plans often study the effects of earlier immunity, use of antiviral drugs,
vaccination strategies and non-pharmaceutical measures such as the closure of schools and the isolation of infected
persons. The pandemic outcome measures are usually incidence of infection, hospitalization, intensive care and death
(27). However, international and national preparedness plans should be expanded such that these models also illustrate
how nonpharmaceutical and pharmaceutical interventions can prevent social inequality in morbidity and mortality in
new pandemics, thus saving lives and limiting social and economic losses. In this way, international health institutions
and national public health institutes will also work to put social inequality in infectious diseases such as influenza on
28.6.2017 | Social inequality – a forgotten factor in pandemic influenza preparedness | Tidsskrift for Den norske legeforening
the agenda along with non-infectious diseases.
As part of the initiative, influenza researchers and pandemic groups at the international health institutions and national
public health institutes – which normally consist of doctors or professionals with backgrounds in other health
disciplines and science disciplines – should collaborate with or recruit pandemic historians and social scientists who
research influenza pandemics. If medical and natural scientists, social scientists and historians work together to develop
common issues, theories, frameworks and languages – including joint analyses and publications – this will generate
more robust and tenable empirical and theoretical results than when they work individually (32). In order to conduct
high-quality epidemiological research on the Spanish influenza, for example, it is not enough just to have a good
understanding of the influenza virus, immunity and virulence; researchers also need to be aware of the historical
context in which data was collected and produced, and take into account that the events of the time, such as World War
I, may have affected the pandemic outcomes (33, 34). For example, the refugee camps in Europe, the Middle East and
North Africa that sprang up during the recent migration and refugee crisis are at a high risk of becoming a breeding
ground for the spread of disease if a new influenza pandemic were to break out today. A holistic research approach to
historical influenza pandemics and transdisciplinary collaboration in the development of pandemic plans will mean
more robust research and will have a long-term influence on the formulation of influenza pandemic preparedness
policy.
Social conditions as an indicator for pandemic vaccines?
Based on the research showing that there are clear social disparities in the pandemic mortality rate (6, 9–12), it is natural
to recommend changes in the vaccination policy on the basis of social conditions in addition to biomedical priorities
for pandemic vaccination. This requires the development of good social indicators. For Norway’s part, the following
groups are assumed to be at risk: those on long-term sick leave, disability benefit claimants and those with a reduced
ability to work, i.e. people with complex social and/or health challenges. Other examples are people with a low level of
education and low income (16). The health authorities in most countries currently translate the international
biomedical recommendations for influenza vaccination into their own national context. The social conditions for
recommending vaccination therefore need to be investigated and determined nationally. Globally, there is no doubt
that prioritizing poor countries in relation to the distribution of scarce pandemic vaccines will have the greatest impact
on reducing social and economic consequences.
Towards a paradigm shift in vaccination strategies against influenza?
In order to aid the international goals of reducing social inequality in health and ensuring good health for all by 2030,
preparedness plans should be revised to reflect the need to avoid the socially unjust burden of disease in future
influenza pandemics. A broader indication of influenza vaccination, based on both social and biomedical conditions,
will have greater potential to reduce the risk of death than if only the biomedical indications are used. Such a change,
where social conditions have implications for vaccination recommendations, would be a paradigm shift in the policy to
combat influenza.
A transdisciplinary approach to the study of influenza pandemics and the preparation of preparedness plans, in which
social and biomedical conditions are taken into account simultaneously, can also inspire research and formulation of
policy that can help reduce social inequality in pandemic threats that are not related to influenza, thereby lessening the
social and economic consequences.
REFERANSER:
1. World Bank. World Bank Group Global Crisis Response Platform. 24 August 2016.
http://documents.worldbank.org/curated/en/334721474058771487/World-Bank-Group-global-crisis-response-platform (8.5.2017).
2. Regjeringen. Norge i global koalisjon for forebygging av epidemier og pandemier. https://regjeringen.no/no/aktuelt/cepi/id2527201/
(18.1.2017).
3. Langberg ØK, Braathen F. - Bill Gates’ skrekkscenario er millioner av døde. Nå åpner han og regjeringen lommeboken for å utvikle
vaksiner i Norge. Aftenposten.
http://www.aftenposten.no/okonomi/Bill-Gates-skrekkscenario-er-millioner-av-dode-Na-apner-han-og-regjeringen-lommeboken-for-a
-utvikle-vaksiner-i-Norge-613057b.html (18.1.2017).
28.6.2017 | Social inequality – a forgotten factor in pandemic influenza preparedness | Tidsskrift for Den norske legeforening
4. Johnson NP, Mueller J. Updating the accounts: global mortality of the 1918-1920 “Spanish” influenza pandemic. Bull Hist Med 2002;
76: 105 - 15. [PubMed][CrossRef]
5. Mamelund S-E. Influenza, Historical. International Encyclopedia of Public Health. 3. San Diego, CA: Academic Press, 2008: 597-609.
6. Simonsen L, Spreeuwenberg P, Lustig R et al. Global mortality estimates for the 2009 Influenza Pandemic from the GLaMOR project:
a modeling study. PLoS Med 2013; 10: e1001558. [PubMed][CrossRef]
7. Shanks GD, Brundage JF. Pathogenic responses among young adults during the 1918 influenza pandemic. Emerg Infect Dis 2012; 18:
201 - 7. [PubMed][CrossRef]
8. Miller MA, Viboud C, Balinska M et al. The signature features of influenza pandemics–implications for policy. N Engl J Med 2009;
360: 2595 - 8. [PubMed][CrossRef]
9. Murray CJ, Lopez AD, Chin B et al. Estimation of potential global pandemic influenza mortality on the basis of vital registry data
from the 1918-20 pandemic: a quantitative analysis. Lancet 2006; 368: 2211 - 8. [PubMed][CrossRef]
10. Mamelund S-E. A socially neutral disease? Individual social class, household wealth and mortality from Spanish influenza in two
socially contrasting parishes in Kristiania 1918-19. Soc Sci Med 2006; 62: 923 - 40. [PubMed][CrossRef]
11. Grantz KH, Rane MS, Salje H et al. Disparities in influenza mortality and transmission related to sociodemographic factors within
Chicago in the pandemic of 1918. Proc Natl Acad Sci U S A 2016; 113: 13839 - 44. [PubMed][CrossRef]
12. Rutter PD, Mytton OT, Mak M et al. Socio-economic disparities in mortality due to pandemic influenza in England. Int J Public
Health 2012; 57: 745 - 50. [PubMed][CrossRef]
13. EU. Health inequalities in the EU — Final report of a consortium. 2013.
http://ec.europa.eu/health//sites/health/files/social_determinants/docs/healthinequalitiesineu_2013_en.pdf (8.5.2017).
14. WHO. Rio political declaration on social determinants of health. World conference on social determinants of health 2011.
http://www.who.int/sdhconference/declaration/en/ (8.5.2017).
15. WHO. Closing the gap in a generation. Health equity through action on the social determinants of health 2008.
http://apps.who.int/iris/bitstream/10665/43943/1/9789241563703_eng.pdf (8.5.2017).
16. Dahl E, Bergsli H, van der Wel KA. Sosial ulikhet i helse: En norsk kunnskapsoversikt. Oslo: Høgskolen i Oslo og Akershus, 2014.
17. Office of Disease Prevention and Health Promotion. Healthy People 2020. https://healthypeople.gov/ (11.4.2017).
18. European Union. One Health: addressing health risks at the interface between animals, humans, and their environments.
http://eeas.europa.eu/health/pandemic_readiness/index_en.htm (8.2.2017).
19. Centers for Disease Control and Prevention. OneHealth. www.cdc.gov/onehealth/ (10.3.2017).
20. World Bank. Pandemic risk and One Health. October 23, 2013.
http://www.worldbank.org/en/topic/health/brief/pandemic-risk-one-health (8.5.2017).
21. World Bank Group launches groundbreaking financing facility to protect poorest countries against pandemics. May 21 2016.
http://www.worldbank.org/en/news/press-release/2016/05/21/world-bank-group-launches-groundbreaking-financingfacility-to-protect
-poorest-countries-against-pandemics (8.5.2017).
22. United Nations. Transforming our world: The 2030 agenda for sustainable development. 2015.
https://sustainabledevelopment.un.org/post2015/ transformingourworld (8.5.2017).
23. Holloway R, Rasmussen SA, Zaza S et al. Updated preparedness and response framework for influenza pandemics. MMWR Recomm
Rep 2014; 63: 1 - 18. [PubMed]
24. Brahmbhatt M, Jonas O. International cooperative responses to pandemic threats: a critical analysis. Brown J World Aff 2015; XXI:
163 - 78.
25. Garrett TA. Pandemic economics: The 1918 influenza and its modern-day implications. Federal Reserve Bank of St Louis Review
2008; 90: 75 - 93.
26. Charania N, Tsuji L. Recommended mitigation measures for an influenza pandemic in remote and isolated first nations
communities of Ontario, Canada: A community-based participatory research approach. International Indigenous Policy Journal 2014;
5: 1 - 22. [CrossRef]
27. Statsministerens kontor. Nasjonal beredskapsplan for pandemisk influensa.
2014.https://regjeringen.no/no/aktuelt/ny-nasjonal-beredskapsplan-mot-pandemiskinfluensa/id2354619 (8.5.2017).
28. European Centre for Disease Prevention and Control. Influenza pandemic plans 2017.
http://ecdc.europa.eu/en/healthtopics/pandemic_preparedness/national_pandemic_preparedness_plans/pages/influenza_pandemi
28.6.2017 | Social inequality – a forgotten factor in pandemic influenza preparedness | Tidsskrift for Den norske legeforening
c_preparedness_plans.aspx (8.4.2017).
29. Public Health Agency of Canada. Canadian pandemic influenza preparedness: Planning guidance for the health sector 2015.
http://www.phac-aspc.gc.ca/cpip-pclcpi/report-rapport-2015-eng.php#pre (10.3.2017).
30. AGDH. Australian health management plan for pandemic influenza. Australian Government Department of Health. April 2014.
http://www.health.gov.au/internet/main/publishing.nsf/Content/ohp-ahmppi.htm (8.5.2017).
31. Grohskopf LA, Sokolow LZ, Broder KR et al. Prevention and control of seasonal influenza with vaccines. MMWR Recomm Rep 2016;
65: 1 - 54. [PubMed][CrossRef]
32. Rosenfield PL. The potential of transdisciplinary research for sustaining and extending linkages between the health and social
sciences. Soc Sci Med 1992; 35: 1343 - 57. [PubMed][CrossRef]
33. Rosenberg CE. Explaining epidemics and other studies in the history of medicine. Cambridge, New York, NY: Cambridge University
Press; 1992.
34. Holmberg M. The ghost of pandemics past: revisiting two centuries of influenza in Sweden. Med Humanit 2016; XXI: 1 - 7.
Publisert: 29. mai 2017, Nr. , 29. mai 2017, Tidsskr Nor Legeforen2017; :911-913
DOI: 10.4045/tidsskr.17.0273
... Many pandemics mostly occur from natural or bio-terrorism like the present coronavirus 2 (SARS -CoV-2) pandemic, a human immunodeficiency virus that has influenced the use of innovative technology tools to be an essential commodity for human sustainability (Mamelund, 2017). The previous global widespread of infectious diseases have caused global pandemics, such as COVID-19, Ebola, Spanish Flu, Bird Flu, Aids, and Tuberculosis (TB) (World Health Organisation, 2011). ...
... Innovative technologies can be utilized to empower, educate, warn and mobilize health care institutions about how to significantly reduce the impact of infectious diseases on humanity (Mamelund, 2017). For example, countries that belong to North Atlantic Treaty Organization (NATO) have adopted measures to respond to pandemic situations (WHO, 2011). ...
Using Information Technology Advancements to Adapt to Global Pandemics A volume in the Advances in Information Quality and Management (AIQM) Book Series
Book
Full-text available
  • Dec 2022
Many organizations, including government institutions and agencies, continue to increase their financial investment on information technology (IT) solutions. Despite these investments, during the global pandemic, employees and managers are either struggling or unequipped to use these tools effectively and efficiently for sustainability, competitive advantage, and decision making. Due to global pandemics, companies must harness the power of various digital channels such as big data analytics and artificial intelligence to better serve their customers and business partners. Using Information Technology Advancements to Adapt to Global Pandemics provides insights and understanding on how companies and organizations are using advances in IT to adapt to global pandemics such as COVID-19. It explores how the various IT approaches can be used for strategic purposes. Covering topics such as higher education institutions, religious organizations, and telework, this premier reference source is an essential resource for government officials, business leaders and managers, industry professionals, IT specialists, policymakers, libraries, academicians, students, and researchers. Source: Publisher
View
... Second, in October 2021 we employed a more detailed structure term search in PubMed (((influenza OR flu) AND pandemic) AND (health AND (disparities OR inequalities OR inequities))), netting 159 articles which were screened for inclusion by AD and ASM. Third, we further reviewed three reviews of the literature that we found during the previous searches and that focused on specific disparities in specific influenza pandemics 22,23,34 , and screened their respective reference lists for inclusion of new papers. ...
Health disparities in past influenza pandemics: A scoping review of the literature
Article
Full-text available
  • Dec 2022
Objective The COVID-19 pandemic has exacerbated existing health disparities. To provide a historical perspective on health disparities for pandemic acute respiratory viruses, we conducted a scoping review of the public health literature of health disparities in influenza outcomes during the 1918, 1957, 1968, and 2009 influenza pandemics. Methods We searched for articles examining socioeconomic or racial/ethnic disparities in any population, examining any influenza-related outcome (e.g., incidence, hospitalizations, mortality), during the 1918, 1957, 1968, and 2009 influenza pandemics. We conducted a structured search of English-written articles in PubMed supplemented by a snowball of articles meeting inclusion criteria. Results A total of 29 articles met inclusion criteria, all but one focusing exclusively on the 1918 or 2009 pandemics. Individuals of low socioeconomic status, or living in low socioeconomic status areas, experienced higher incidence, hospitalizations, and mortality in the 1918 and 2009 pandemics. There were conflicting results regarding racial/ethnic disparities during the 1918 pandemic, with differences in magnitude and direction by outcome, potentially due to issues in data quality by race/ethnicity. Racial/ethnic minorities had generally higher incidence, mortality, and hospitalization rates in the 1957 and 2009 pandemics. Conclusion Individuals of low socioeconomic status and racial/ethnic minorities have historically experienced worse influenza outcomes during pandemics. These historical patterns can inform current research to understand disparities in the ongoing COVID-19 pandemic and future pandemics.
View
... To address significant local and global issues, traditionally separate and often seemingly disparate disciplines must converge, forming new networks, partnerships, and bodies of knowledge. Also emergent was the essential recognition that many of the most pressing problems and their solutions are embedded within social and cultural contexts that bear the signatures of inequity, injustice, and limits to accessibility (e.g., Downs, 1970;McLeman & Smit, 2006;Mamelund, 2017;O'Brien & Leichenko, 2000;Saiz, 2009;Watts & Bohle, 1993). Addressing contemporary problems requires innovative education and research, and students must prepare for professional (and personal) lives in an increasingly convergent world. ...
View
... Societies with lower levels of social and economic inequality are better prepared to respond to most crises. [5][6][7] Governments have a duty to combat poverty, to ensure that everyone receives the economic, social, health-related, and psychological support that they need. When people are economically safe it is also easier for them to support others, and to comply with crisis management measures. ...
View
... Societies with lower levels of social and economic inequality are better prepared to respond to most crises. [5][6][7] Governments have a duty to combat poverty, to ensure that everyone receives the economic, social, health-related, and psychological support that they need. When people are economically safe it is also easier for them to support others, and to comply with crisis management measures. ...
Values in challenging times: Strategic crisis management in the EU
Article
This Comment draws upon the European Group on Ethics in Science and New Technologies' Statement on "Values in Times of Crisis: Strategic crisis management in the EU", which is available here: https://research-and-innovation.ec.europa.eu/system/files/2022-11/ec_rtd_sam-crisis-management-ege-statement.pdf (November 2022)
View
... Outro estudo demonstrou que a taxa de infecção por Covid-19 é três vezes maior em municípios predominantemente negros do que em municípios predominantemente brancos, e a taxa de mortalidade é seis vezes maior (Abrams & Szefler, 2020). Além disso, ao analisar a história associada às grandes epidemias que assolaram o globo, como gripe espanhola, H1N1 e SARS foi evidenciado que as desigualdades sociais estão intrinsecamente relacionadas a maior taxa de transmissão e severidade dessas doenças (Mamelund, 2017). Além disso, uma tragédia como a pandemia do COVID-19 torna os pais e cuidadores mais estressados, temerosos e preocupados com questões relacionadas saúde e atividades econômicas, especialmente em países em desenvolvimento (Medrado et al, 2021;Silva et al, 2022). ...
Estresse tóxico e sua influência sobre a infância e adolescência durante a pandemia COVID-19: um comparativo em escolas públicas e privada do município de Paulo Afonso-BA
Article
Full-text available
  • Aug 2022
Objetivo: avaliar o impacto da pandemia por COVID-19 como fator desencadeante de estresse tóxico na infância, quais áreas que sofreram maiores alterações e realizar um comparativo do impacto desse período em crianças de diferentes classes sociais. Métodologia: aplicação de questionários online para os pais ou responsáveis pelas crianças, em escolas do município de Paulo Afonso-BA. Resultados: constata-se que com o avançar da idade, crianças e adolescentes apresentaram 6,8 vezes mais chance de manifestar mudança negativa na rotina durante o período da pandemia e que estudantes do ensino público apresentaram 5,58 vezes mais chance de serem afetadas negativamente por esse momento. Conclusão: o presente artigo demonstrou o impacto negativo gerado pela pandemia de COVID-19 na saúde das crianças e adolescentes do município de Paulo Afonso-BA, afetando desproporcionalmente aqueles matriculados em instituições públicas e com idades mais avançadas. Foi possível identificar a associação existente entre queda do rendimento escolar com a introspecção e a interrupção da prática de exercícios físicos nessa população. Torna-se evidente a necessidade de investimento em maiores estudos acerca do tema.
View
... However, overcrowding, a lack of access to adequate water and sanitation, a lack of medical resources, and pre-existing risk factors (i.e., poor health) plague a large proportion of households and individuals in developing countries [1]. A growing number of studies, mainly from OECD countries, found that the risk of infection and death from COVID-19 was disproportionately higher for people with a disadvantaged socioeconomic status (SES) [2][3][4][5]. Disparities in the capacity to implement NPIs and pre-existing health risk factors are proposed as the primary mechanisms for social inequalities in pandemic morbidity and mortality [6,7]. Due to a lack of data on individual-level COVID-19 infection and mortality, research examining societal disparities in COVID-19 risk factors and NPI compliance is mainly limited to OECD countries. ...
Socioeconomic-Related Inequalities in COVID-19 Vulnerability in South Africa
Article
Full-text available
Individuals’ vulnerability to the risk of COVID-19 infection varies due to their health, socioeconomic, and living circumstances, which also affect the effectiveness of implementing non-pharmacological interventions (NPIs). In this study, we analysed socioeconomic-related inequalities in COVID-19 vulnerability using data from the nationally representative South African General Household Survey 2019. We developed a COVID-19 vulnerability index, which includes health and social risk factors for COVID-19 exposure and susceptibility. The concentration curve and concentration index were used to measure socioeconomic-related inequalities in COVID-19 vulnerability. Recentred influence function regression was then utilised to decompose factors that explain the socioeconomic-related inequalities in COVID-19 vulnerability. The concentration index estimates were all negative and highly significant (p < 0.01), indicating that vulnerability to COVID-19 was more concentrated among the poor. According to the decomposition analysis, higher income and education significantly (p < 0.01) positively impacted lowering socioeconomic-related COVID-19 vulnerability. Living in an urban region, being Black, and old all had significant (p < 0.01) positive impacts on increasing socioeconomic-related COVID-19 vulnerability. Our findings contribute to a better understanding of socially defined COVID-19-vulnerable populations in South Africa and the implications for future pandemic preparedness plans.
View
Biocultural perspectives on bioarchaeological and paleopathological evidence of past pandemics
Article
  • Nov 2022
Objectives Pandemics have profoundly impacted human societies, but until relatively recently were a minor research focus within biological anthropology, especially within biocultural analyses. Here, we explore research in these fields, including molecular anthropology, that employs biocultural approaches, sometimes integrated with intersectionality and ecosocial and syndemic theory, to unpack relationships between social inequality and pandemics. A case study assesses the 1918 influenza pandemic's impacts on the patient population of the Mississippi State Asylum (MSA). Materials and Methods We survey bioarchaeological and paleopathological literature on pandemics and analyze respiratory disease mortality relative to sex, age, and social race amongst patient deaths (N = 2258) between 1912 and 1925. Logistic regression models were used to assess relationships between cause of death and odds of death during the pandemic (1918–1919). Results Findings include substantial respiratory mortality during the pandemic, including from influenza and influenza syndemic with pneumonia. Older patients (40–59 years, 60+ years) had lower odds (p < 0.01) of dying from respiratory disease than younger patients, as did female patients compared to males (p < 0.05). Age patterns are broadly consistent with national and state trends, while elevated mortality amongst Black and/or African American patients may reflect intersections between gender roles and race-based structural violence in the Jim Crow South. Discussion Future work in biological anthropology on past pandemics may benefit from explicit incorporation of biocultural frameworks, intersectionality, and ecosocial and syndemic theory. Doing so enables holistic analyses of interactions between social context, social inequality and pandemic outcomes, generating data informative for public health responses and pandemic preparedness.
View
Use of automated machine learning for an outbreak risk prediction tool
Article
  • Oct 2022
The frequency of serious epidemics has continued to increase in the last decade. The ability to predict the risk of outbreaks can improve prevention and control. There are few prediction models available, and of these most are manually constructed by human experts. These manual models are affected by the lack of automation and have limitations in data processing. They can be enhanced with modern machine-learning techniques. Machine learning (ML) based prediction models, however, have higher requirement for professional knowledge and are not broadly accessible to researchers who do not have ML expertise. We proposed automated machine learning (AutoML) as an advanced solution. It automates the entire ML design process for users without requiring ML knowledge, therefore allows non-ML experts to individually build ML models. To demonstrate the functionality of AutoML to develop reliable systems, we expanded an existing manually developed risk analysis model, EPIRISK, that uses economic, social and medical risk factors to predict epidemic risk. Using the AutoML platform BrewAI, we obtained an automatically generated ML model to predict epidemic risk. This was compared with six traditionally built machine learning models. The AutoML tool generated a model of 77% accuracy in predicting risk. It had similar accuracy to the six traditional built ML models. Such tools are easy to use and could make ML models more accessible to non-ML experts.
View
View
Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918
Article
Full-text available
  • Nov 2016
Significance The pervasiveness of influenza among humans and its rapid spread during pandemics create a false sense that all humans are affected equally. In this work, we show that neighborhood-level social determinants were associated with greater burdens of pandemic influenza in 1918 and several other diseases in a major US city. We show that literacy, homeownership, and unemployment were associated with cumulative influenza mortality as well as measures of the speed of transmission using a unique dataset describing the home location and week of death of individuals who died during the influenza pandemic in 1918. Our results suggest that, similar to other infectious diseases, social disparities should be a focus of research and public health response in future pandemics.
View
The ghost of pandemics past: Revisiting two centuries of influenza in Sweden
Article
Full-text available
  • Nov 2016
Previous influenza pandemics are usually invoked in pandemic preparedness planning without a thorough analysis of the events surrounding them, what has been called the ‘configuration’ of epidemics. Historic pandemics are instead used to contrast them to the novelty of the coming imagined plague or as fear of a ghost-like repetition of the past. This view of pandemics is guided by a biomedical framework that is ahistorical and reductionist. The meaning of ‘pandemic’ influenza is in fact highly ambiguous in its partitioning of pandemic and seasonal influenza. The past 200 years of influenza epidemics in Sweden are examined with a special focus on key social structures—households, schools, transportations and the military. These are shown to have influenced the progression of influenza pandemics. Prevailing beliefs around influenza pandemics have also profoundly influenced intervention strategies. Measuring long-term trends in pandemic severity is problematic because pandemics are non-linear events where the conditions surrounding them constantly change. However, in a linearised view, the Spanish flu can be seen to represent a historical turning point and the H1N1 2009 pandemic not as an outlier, but following a 100-year trend of decreasing severity. Integrating seasonal and pandemic influenza, and adopting an ecosocial stance can deepen our understanding and bring the ghost-like pandemic past to life.
View
Prevention and Control of Seasonal Influenza with Vaccines: Recommendations of the Advisory Committee on Immunization Practices — United States, 2016–17 Influenza Season
Article
Full-text available
  • Aug 2016
This report updates the 2015-16 recommendations ofthe Advisoiy Committee on Immunization Practices (ACIP) regarding the use of seasonal influenza vaccines (Grohskopf LA, Sokolow LZ, Olsen SJ, Bresee JS, Broder KR, Karron RA. Prevention and control of influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices, United States, 2015-16 influenza season. MMWR Morb Mortal Wkly Rep 2015;64:818-25). Routine annual influenza vaccination is recommended for all persons aged months who do not have contraindications. For the 2016-17 influenza season, inactivated influenza vaccines (IIVs) will be available in both trivalent (IIV3) and quadrivalent (IIV4) formulations. Recombinant influenza vaccine (RIV) will be available in a trivalent formulation (RIV3). In light of concerns regarding low effectiveness against influenza A(H1N1)pdm09 in the United States during the 2013-14 and 2015-16 seasons, for the 2016-17 season, ACIP makes the interim recommendation that live attenuated influenza vaccine (LAIV4) should not be used. Vaccine virus strains included in the 2016-17 U.S. trivalent influenza vaccines will be an A/California/7/2009 (H1N1) like virus, an A/Hong Kong/4801/2014 (H3N2) like virus, and a B/Brisbane/60/2008 like virus (Victoria lineage). Quadrivalent vaccines will include an additional influenza B virus strain, a B/Phuket/3073/2013 like virus (Yamagata lineage). Recommendations for use of different vaccine types and specific populations are discussed. A licensed, age -appropriate vaccine should be used. No preferential recommendation is made for one influenza vaccine product over another for persons for whom more than one licensed, recommended product is otherwise appropriate. This information is intended for vaccination providers, immunization program personnel, and public health personnel. Information in this report reflects discussions during public meetings ofACIP held on October 21, 2015; February 24, 2016; andJune 22, 2016 These recommendations apply to all licensed influenza vaccines used within Food and DrugAdministration licensed indications, including those licensed after the publication of this report. Updates and other information are available at CDC's influenza website (http://www.cdc.govfflit). Vaccination and health care providers should check CDC's influenza website periodically for additional information.
View
View
Recommended Mitigation Measures for an Influenza Pandemic in Remote and Isolated First Nations Communities of Ontario, Canada: A Community-Based Participatory Research Approach
Article
Full-text available
  • Jun 2014
Influenza pandemics disproportionately impact remote and/or isolated Indigenous communities worldwide. The differential risk experienced by such communities warrants the recommendation of specific mitigation measures. Interviewer-administered questionnaires were conducted with adult key health care informants from three remote and isolated Canadian First Nations communities of sub-Arctic Ontario. Forty-eight mitigation measures (including the setting, pandemic period, trigger, and duration) were questioned. Participants’ responses were summarized and collected data were deductively and inductively coded. The participants recommended 41 of the questioned mitigation measures, and often differed from previous literature and national recommendations. Results revealed that barriers, such as overcrowded housing, limited supplies, and health care infrastructure, impacted the feasibility of implementing mitigation measures. These findings suggest that pandemic plans should recommend control strategies for remote and isolated Canadian First Nations communities that may not be supported in other communities. These findings highlight the importance of engaging locally impacted populations using participatory approaches in policy decision-making processes. Other countries with remote and/or isolated Indigenous communities are encouraged to include recommendations for mitigation measures that specifically address the unique needs of such communities in an effort to improve their health outcomes during the next influenza pandemic.
View
Updated Preparedness and Response Framework for Influenza Pandemics
Article
Full-text available
  • Sep 2014
The complexities of planning for and responding to the emergence of novel influenza viruses emphasize the need for systematic frameworks to describe the progression of the event; weigh the risk of emergence and potential public health impact; evaluate transmissibility, antiviral resistance, and severity; and make decisions about interventions. On the basis of experience from recent influenza responses, CDC has updated its framework to describe influenza pandemic progression using six intervals (two prepandemic and four pandemic intervals) and eight domains. This updated framework can be used for influenza pandemic planning and serves as recommendations for risk assessment, decision-making, and action in the United States. The updated framework replaces the U.S. federal government stages from the 2006 implementation plan for the National Strategy for Pandemic Influenza (US Homeland Security Council. National strategy for pandemic influenza: implementation plan. Washington, DC: US Homeland Security Council; 2006. Available at http://www.flu.gov/planning-preparedness/federal/pandemic-influenza-implementation.pdf). The six intervals of the updated framework are as follows: 1) investigation of cases of novel influenza, 2) recognition of increased potential for ongoing transmission, 3) initiation of a pandemic wave, 4) acceleration of a pandemic wave, 5) deceleration of a pandemic wave, and 6) preparation for future pandemic waves. The following eight domains are used to organize response efforts within each interval: incident management, surveillance and epidemiology, laboratory, community mitigation, medical care and countermeasures, vaccine, risk communications, and state/local coordination. Compared with the previous U.S. government stages, this updated framework provides greater detail and clarity regarding the potential timing of key decisions and actions aimed at slowing the spread and mitigating the impact of an emerging pandemic. Use of this updated framework is anticipated to improve pandemic preparedness and response in the United States. Activities and decisions during a response are event-specific. These intervals serve as a reference for public health decision-making by federal, state, and local health authorities in the United States during an influenza pandemic and are not meant to be prescriptive or comprehensive. This framework incorporates information from newly developed tools for pandemic planning and response, including the Influenza Risk Assessment Tool and the Pandemic Severity Assessment Framework, and has been aligned with the pandemic phases restructured in 2013 by the World Health Organization.
View
Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study
Article
Full-text available
Background Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries.Methods and findingsWe obtained weekly virology and underlying cause-of-death mortality time series for 2005-2009 for 20 countries covering ∼35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%-85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000-249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons
View
Pathogenic Responses among Young Adults during the 1918 Influenza Pandemic
Article
Full-text available
  • Feb 2012
Of the unexplained characteristics of the 1918-19 influenza pandemic, the extreme mortality rate among young adults (W-shaped mortality curve) is the foremost. Lack of a coherent explanation of this and other epidemiologic and clinical manifestations of the pandemic contributes to uncertainty in preparing for future pandemics. Contemporaneous records suggest that immunopathologic responses were a critical determinant of the high mortality rate among young adults and other high-risk subgroups. Historical records and findings from laboratory animal studies suggest that persons who were exposed to influenza once before 1918 (e.g., A/H3Nx 1890 pandemic strain) were likely to have dysregulated, pathologic cellular immune responses to infections with the A/H1N1 1918 pandemic strain. The immunopathologic effects transiently increased susceptibility to ultimately lethal secondary bacterial pneumonia. The extreme mortality rate associated with the 1918-19 pandemic is unlikely to recur naturally. However, T-cell-mediated immunopathologic effects should be carefully monitored in developing and using universal influenza vaccines.
View
View
International encyclopedia of public health
Book
  • Jan 2008
An authoritative and comprehensive guide to the major issues, challenges, methods, and approaches of global public health. This encyclopedia will cover all dimensions of the field, from details of specific diseases to the organization of social insurance agencies. A significant percentage of the articles will cover public health aspects of diseases and conditions. Other articles will survey aging, diet, injuries, ethical and legal subjects in public health, measurement and modeling, consumerism, anthropology and sociology, economics, the history of public health, and global issues.
View