On the Current Connection and Relation Between Health Informatics and Social Informatics.

Scholars from the health and medical sciences have recently proposed the term social informatics (SI) as a new scientific subfield of health informatics (HI). However, SI is not a new academic concept; in fact, it has been continuously used in the social sciences and informatics since the 1970s. Although the dominant understanding of SI was established in the 1990s in the United States, a rich international perspective on SI has existed since the 1970s in other regions of the world. When that perspective is considered, the fields of understanding can be structured into 7 SI schools of thought. Against that conceptual background, this paper contributes to the discussion on the relationship between SI and HI, outlining possible perspectives of SI that are associated with health, medical, and clinical aspects. This paper argues against the multiplication and inconsistent appearance of the term SI when newly used in health and medical sciences. A more explicit name for the area that uses health and social data to advance individual and population health might be helpful to overcome this issue; giving an identity to this new field would help it to be understood more precisely and bring greater separation. This labeling could be fruitful for further segmentation of HI, which is rapidly expanding.

Seroprevalence of severe acute respiratory syndrome coronavirus 2 in Slovenia: results of two rounds of a nationwide population study on a probability-based sample, challenges and lessons learned.

OBJECTIVES: Seroprevalence surveys provide crucial information on cumulative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure. This Slovenian nationwide population study is the first longitudinal 6-month serosurvey using probability-based samples across all age categories. METHODS: Each participant supplied two blood samples: 1316 samples in April 2020 (first round) and 1211 in October/November 2020 (second round). The first-round sera were tested using Euroimmun Anti-SARS-CoV-2 ELISA IgG (ELISA) and, because of uncertain estimates, were retested using Elecsys Anti-SARS-CoV-2 (Elecsys-N) and Elecsys Anti-SARS-CoV-2 S (Elecsys-S). The second-round sera were concomitantly tested using Elecsys-N/Elecsys-S. RESULTS: The populations of both rounds matched the overall population (n = 3000), with minor settlement type and age differences. The first-round seroprevalence corrected for the ELISA manufacturer's specificity was 2.78% (95% highest density interval [HDI] 1.81%-3.80%), corrected using pooled ELISA specificity calculated from published data 0.93% (95% CI 0.00%-2.65%), and based on Elecsys-N/Elecsys-S results 0.87% (95% HDI 0.40%-1.38%). The second-round unadjusted lower limit of seroprevalence on 11 November 2020 was 4.06% (95% HDI 2.97%-5.16%) and on 3 October 2020, unadjusted upper limit was 4.29% (95% HDI 3.18%-5.47%). CONCLUSIONS: SARS-CoV-2 seroprevalence in Slovenia increased four-fold from late April to October/November 2020, mainly due to a devastating second wave. Significant logistic/methodological challenges accompanied both rounds. The main lessons learned were a need for caution when relying on manufacturer-generated assay evaluation data, the importance of multiple manufacturer-independent assay performance assessments, the need for concomitant use of highly-specific serological assays targeting different SARS-CoV-2 proteins in serosurveys conducted in low-prevalence settings or during epidemic exponential growth and the usefulness of a Bayesian approach for overcoming complex methodological challenges.