Category: Publications

We have just published our second paper which is part of our 2022-23 academic year project at the Centre for Advanced Study Social Science Meets Biology: Indigenous People and Severe Influenza Outcomes – CAS. You can read the whole paper here: Investigating COVID-19 transmission and mortality differences between indigenous and non-indigenous populations in Mexico – International Journal of Infectious Diseases (ijidonline.com)

Highlights

• Indigenous groups had a 68% higher COVID-19 mortality rate than the non-indigenous groups.
• Of 32 federal entities, 23 had a higher mortality rate among the indigenous groups.
• The mortality rate ratio and the reproduction number were highest during the fourth wave of the COVID-19 pandemic.
• Indigenous populations had a higher care-seeking delay than the non-indigenous populations.
• The hazard ratio decreased from 1.67 (unadjusted) to 1.08 in the adjusted model.

Abstract

Objectives

Indigenous populations have been disproportionately affected during pandemics. We investigated COVID-19 mortality estimates among indigenous and non-indigenous populations at national and sub-national levels in Mexico.

Methods

We obtained data from the Ministry of Health, Mexico, on 2,173,036 laboratory-confirmed RT-PCR positive COVID-19 cases and 238,803 deaths. We estimated mortality per 1000 person-weeks, mortality rate ratio (RR) among indigenous vs. non-indigenous groups, and hazard ratio (HR) for COVID-19 deaths across four waves of the pandemic, from February 2020 to March 2022. We also assessed differences in the reproduction number (Rt).

Results

The mortality rate among indigenous populations of Mexico was 68% higher than that of non-indigenous groups. Out of 32 federal entities, 23 exhibited higher mortality rates among indigenous groups (P < 0.05 in 13 entities). The fourth wave showed the highest RR (2.40). The crude HR was 1.67 (95% CI: 1.62, 1.72), which decreased to 1.08 (95% CI: 1.04, 1.11) after controlling for other covariates. During the intense fourth wave, the Rt among the two groups was comparable.

Conclusion

Indigenous status is a significant risk factor for COVID-19 mortality in Mexico. Our findings may reflect disparities in non-pharmaceutical (e.g., handwashing and using facemasks), and COVID-19 vaccination interventions among indigenous and non-indigenous populations in Mexico.

You can read the new paper here: Disparities in the offer of COVID-19 vaccination to migrants and non-migrants in Norway: a cross sectional survey study | BMC Public Health | Full Text (biomedcentral.com)

Vaccination is key to reducing the spread and impacts of COVID-19 and other infectious diseases. Migrants, compared to majority populations, tend to have lower vaccination rates, as well as higher infection disease burdens. Previous studies have tried to understand these disparities based on factors such as misinformation, vaccine hesitancy or medical mistrust. However, the necessary precondition of receiving, or recognizing receipt, of an offer to get a vaccine must also be considered.

Methods

We conducted a web-based survey in six parishes in Oslo that have a high proportion of migrant residents and were hard-hit during the COVID-19 pandemic. Logistic regression analyses were conducted to investigate differences in reporting being offered the COVID-19 vaccine based on migrant status. Different models controlling for vaccination prioritization variables (age, underlying health conditions, and health-related jobs), socioeconomic and demographic variables, and variables specific to migrant status (language spoken at home and years lived in Norway) were conducted.

Results

Responses from 5,442 participants (response rate of 9.1%) were included in analyses. The sample included 1,284 (23.6%) migrants. Fewer migrants than non-migrants reported receiving a vaccine offer (68.1% vs. 81.1%), and this difference was significant after controlling for prioritization variables (OR 0.65, 95% CI: 0.52–0.82). Subsequent models showed higher odds ratios for reporting having been offered the vaccine for females, and lower odds ratios for those with university education. There were few to no significant differences based on language spoken at home, or among birth countries compared to each other. Duration of residence emerged as an important explanatory variable, as migrants who had lived in Norway for fewer than 15 years were less likely to report offer of a vaccine.

Conclusion

Results were consistent with studies that show disparities between non-migrants and migrants in actual vaccine uptake. While differences in receiving an offer cannot fully explain disparities in vaccination rates, our analyses suggest that receiving, or recognizing and understanding, an offer does play a role. Issues related to duration of residence, such as inclusion in population and health registries and health and digital literacy, should be addressed by policymakers and health services organizers.

Nan Zou Bakkeli at PANSOC and Consumption Reserch Norway has just published a new paper in the journal “Social Science Computer Review”. You can read it here: Predicting Psychological Distress During the COVID-19 Pandemic: Do Socioeconomic Factors Matter? – Nan Zou Bakkeli, 2022 (sagepub.com)

The COVID-19 pandemic has posed considerable challenges to people’s mental health, and the prevalence of anxiety and depression increased substantially during the pandemic. Early detection of potential depression is crucial for timely preventive interventions; therefore, there is a need for depression prediction.

This study was based on survey data collected from 5001 Norwegians (3001 in 2020 and 2000 in 2021). Machine learning models were used to predict depression risk and to select models with the best performance for each pandemic phase. Probability thresholds were chosen based on cost-sensitive analysis, and measures such as accuracy (ACC) and the area under the receiver operating curve (AUC) were used to evaluate the models’ performance.

The study found that decision tree models and regularised regressions had the best performance in both 2020 and 2021. For the 2020 predictions, the highest accuracies were obtained using gradient boosting machines (ACC = 0.72, AUC = 0.74) and random forest algorithm (ACC = 0.71, AUC = 0.75). For the 2021 predictions, the random forest (ACC = 0.76, AUC = 0.78) and elastic net regularisation (ACC = 0.76, AUC = 0.78) exhibited the best performances. Highly ranked predictors of depression that remained stable over time were self-perceived exposure risks, income, compliance with nonpharmaceutical interventions, frequency of being outdoors, contact with family and friends and work–life conflict. While epidemiological factors (having COVID symptoms or having close contact with the infected) influenced the level of psychological distress to a larger extent in the relatively early stage of pandemic, the importance of socioeconomic factors (gender, age, household type and employment status) increased substantially in the later stage.Conclusion: Machine learning models consisting of demographic, socioeconomic, behavioural and epidemiological features can be used for fast ‘first-hand’ screening to diagnose mental health problems. The models may be helpful for stakeholders and healthcare providers to provide early diagnosis and intervention, as well as to provide insight into forecasting which social groups are more vulnerable to mental illness in which social settings.

As an OsloMet Centre of Research Excellence, we at PANSOC are so proud to have co-authored an original research article with Swiss colleagues in “Annals of Internal Medicine”. This highly prestigious journal has an impact factor of 25.4 and is considered one of top 5 in medicine together with JAMA, New England Journal of Medicine, The Lancet and The BMJ. You can read the paper here:

Historically High Excess Mortality During the COVID-19 Pandemic in Switzerland, Sweden, and Spain | Annals of Internal Medicine (acpjournals.org)

The new paper is published in Scandinavian Journal of Public Health, see here: https://journals.sagepub.com/doi/full/10.1177/14034948211060635

Abstract

Aims:

This study aimed to estimate the size of the risk group for severe influenza and to describe the social patterning of the influenza risk group in Norway, defined as everyone ⩾65 years of age and individuals of any age with certain chronic conditions (medical risk group).

Methods:

Study data came from a nationally representative survey among 10,923 individuals aged 16–79 years. The medical risk group was defined as individuals reporting one or more relevant chronic conditions. The associations between educational attainment, employment status, age and risk of belonging to the medical risk group were studied with logistic regression.

Results:

Nearly a fifth (19.0%) of respondents reported at least one chronic condition, while 29.4% belonged to the influenza risk group due to either age or chronic conditions. Being older, having a low educational level (comparing compulsory education to higher education, odds ratio (OR)=1.4, 95% confidence interval (CI) 1.2–1.8 among women, and OR=1.3, 95% CI 1.1–1.7 among men) and a weaker connection to working life (comparing disability pension to working full-time, OR=6.8, 95% CI 5.3–8.7 among women, and OR=6.5, 95% CI 4.9–8.5 among men) was associated with a higher risk of belonging to the medical risk group for severe influenza.

Conclusions:

This study indicates that the prevalence of medical risk factors for severe influenza is disproportionally distributed across the socio-economic spectrum in Norway. These results should influence both public funding decisions regarding influenza vaccination and communication strategies towards the public and health professionals.

In this invited paper for the 75 years of Population Studies diamond anniversary special issue, Svenn-Erik Mamelund and Jessica Dimka discuss the mechanisms (differential exposure, susceptibility, and consequences) underlying the mortality and morbidity disparities by socio-economic status and race/ethnicity in the 1918 flu and COVID-19 pandemics, emphasizing the tendency of pandemics to inflate pre-existing health disparities through these means. The authors use both historical and contemporary data and they make the case for thinking about the reduction of health disparities as an important pandemic preparedness strategy. Read full paper here:

Full article: Not the great equalizers: Covid-19, 1918–20 influenza, and the need for a paradigm shift in pandemic preparedness (tandfonline.com)

The the second special issue on the social, economic and health-related consequences of COVID-19 in Scandinavian Journal of Public Health now published! We at PANSOC are proud to have contributed with 2 articles. The new issue is available here: https://journals.sagepub.com/toc/sjpc/49/7Scandinavian Journal of Public Health – Volume 49, Number 7, Nov 01, 2021 (sagepub.com)

This study by Mari Holm Ingelsrud https://www.tandfonline.com/doi/full/10.1080/10301763.2021.1979449 investigates how work-related consequences of COVID-19 in Norway during the first wave varied between workers in different employment arrangements. The generalised linear model (GLM) regressions estimate the relative risk of being directed to work from home, temporarily laid off, having reduced working time and income loss in a representative sample of 3002 workers. The models compare temporarily employed and self-employed workers with permanently employed workers and workers in voluntary and involuntary part-time positions with full-time workers. Results indicate that the self-employed had a higher likelihood of experiencing reduced working time and income loss. Temporary employment did not entail a higher likelihood of any measured outcomes. Part-time workers had a higher chance of income loss and a lower chance of being directed to work from home than full-time workers. Results also indicate that employees in part-time positions had a higher likelihood of having reduced working hours. The findings are discussed with perspectives on flexibility, risk and how standard jobs form regulation and welfare policy. Despite the government’s efforts to increase the safety nets for new groups of workers, our results indicate that the coverage was not wide enough. Thus, illustrating the individual economic risk inherent in non-standard employment relationships.