Background  Immigrants in Sweden, particularly those from low- and middle-income countries, had higher risks of COVID-19 mortality and morbidity compared to the Swedish-born. However, prior studies have not quantified the contribution of the differential distribution of health and social determinants to the increased risks.

Methods  We used total population registers from Sweden to investigate disparities in COVID-19 hospitalization between five groups of immigrants and Swedish-born, using a cohort 577911 working-age adults (18–65 years) living in Stockholm during the first two waves of the COVID-19 pandemic. Applying a decomposition analysis, we quantified the relative contribution of age, sex, income, education, occupation type, residential area, and pre-existing medical conditions to these disparities.

Results  Our study shows that immigrants have higher risks of hospitalization compared to Swedish-born, and that the investigated factors accounted for these disparities to varying degrees across immigrant groups. For the most affected immigrant groups (from Africa and Middle East), the examined factors together account for only a minor part of the disparities (21% and 18% for Wave 1; 16% and 11% for Wave 2), with occupation type and residential area contributing substantially.

Conclusions  Common observable social determinants of health account for a moderate share of the overall disparities in COVID-19 hospitalizations between Swedish-born individuals and immigrant from the most affected regions of origin.

Climate sensitivity of infectious diseases is discussed in many studies. A quantitative basis for distinguishing and predicting the disease impacts of climate and other environmental and anthropogenic driver-pressure changes, however, is often lacking. To assess research effort and identify possible key gaps that can guide further research, we here apply a scoping review approach to two widespread infectious diseases: Lyme disease (LD) as a vector-borne and cryptosporidiosis as a water-borne disease. Based on the emerging publication data, we further structure and quantitatively assess the driver-pressure foci and interlinkages considered in the published research so far. This shows important research gaps for the roles of rarely investigated water-related and socioeconomic factors for LD, and land-related factors for cryptosporidiosis. For both diseases, the interactions of host and parasite communities with climate and other driver-pressure factors are understudied, as are also important world regions relative to the disease geographies; in particular, Asia and Africa emerge as main geographic gaps for LD and cryptosporidiosis research, respectively. The scoping approach developed and gaps identified in this study should be useful for further assessment and guidance of research on infectious disease sensitivity to climate and other environmental and anthropogenic changes around the world.

Recognition of climate-sensitive infectious diseases is crucial for mitigating health threats from climate change. Recent studies have reasoned about potential climate sensitivity of diseases in the Northern/Arctic Region, where climate change is particularly pronounced. By linking disease and climate data for this region, we here comprehensively quantify empirical climate-disease relationships. Results show significant relationships of borreliosis, leptospirosis, tick-borne encephalitis (TBE), Puumala virus infection, cryptosporidiosis, and Q fever with climate variables related to temperature and freshwater conditions. These data-driven results are consistent with previous reasoning-based propositions of climate-sensitive infections as increasing threats for humans, with notable exceptions for TBE and leptospirosis. For the latter, the data imply decrease with increasing temperature and precipitation experienced in, and projected for, the Northern/Arctic Region. This study provides significant data-based underpinning for simplified empirical assessments of the risks of several infectious diseases under future climate change.

Hydroclimatic change may affect the range of some infectious diseases, including tularemia. Previous studies have investigated associations between tularemia incidence and climate variables, with some also establishing quantitative statistical disease models based on historical data, but studies considering future climate projections are scarce. This study has used and combined hydro-climatic projection outputs from multiple global climate models (GCMs) in phase six of the Coupled Model Intercomparison Project (CMIP6), and site-specific, parameterized statistical tularemia models, which all imply some type of power-law scaling with preceding-year tularemia cases, to assess possible future trends in disease outbreaks for six counties across Sweden, known to include tularemia high-risk areas. Three radiative forcing (emissions) scenarios are considered for climate change projection until year 2100, incuding low (2.6 Wm−2), medium (4.5 Wm−2), and high (8.5 Wm−2) forcing. The results show highly divergent changes in future disease outbreaks among Swedish counties, depending primarily on site-specific type of the best-fit disease power-law scaling characteristics of (mostly positive, in one case negative) sub- or super-linearity. Results also show that scenarios of steeper future climate warming do not necessarily lead to steeper increase of future disease outbreaks. Along a latitudinal gradient, the likely most realistic medium climate forcing scenario indicates future disease decreases (intermittent or overall) for the relatively southern Swedish counties Örebro and Gävleborg (Ockelbo), respectively, and disease increases of considerable or high degree for the intermediate (Dalarna, Gävleborg (Ljusdal)) and more northern (Jämtland, Norrbotten; along with the more southern Värmland exception) counties, respectively.

Rapid changes in high-latitude hydroclimate have important implications for human societies and environment. Previous studies of different regions have indicated better agreement between climate model results and observation data for the thermodynamic variable of surface air temperature (T) than for the water variables of precipitation (P), evapotranspiration (ET), and runoff (R). Here we compare climate model output with observations for 64 Nordic and Arctic hydrological basins of different sizes, and for the whole region combined. We find an unexpectedly high agreement between models and observations for R, about as high as the model-observation agreement for T and distinctly higher than that for P or ET. Model-observation agreement for R and T is also consistently higher on the whole-region scale than individual basin scales. In contrast, model-observation agreement for P and ET is overall lower, and for some error measures also lower for the whole region than for individual basins of various scales. Region-specific soil freeze-thaw bias of climate models can at least partly explain the low model-observation agreement for P and ET, while leaving modeled R relatively unaffected. Thereby, model projections for this region may be similarly reliable and directly useful for large-scale average conditions of R as of T.

Hydroclimatic changes may be particularly pronounced in high-latitude regions and can influence infectious diseases, jeopardizing regional human and animal health. In this study, we consider the example of tularemia, one of the most studied diseases in high-latitude regions, which is likely to be impacted by large regional hydroclimatic changes. For this disease case, we use a validated statistical model and develop a method for quantifying possible hydroclimatically driven shifts in outbreak conditions. The results show high sensitivity of tularemia outbreaks to certain combinations of hydroclimatic variable values. These values are within the range of past regional observations and may represent just mildly shifted conditions from current hydroclimatic averages. The methodology developed also facilitates relatively simple identification of possible critical hydroclimatic thresholds, beyond which unacceptable endemic disease levels may be reached. These results call for further research on how projected hydroclimatic changes may affect future outbreaks of tularemia and other infectious diseases in high-latitude and other world regions, with particular focus on critical thresholds to high-risk conditions. More research is also needed on the generality and spatiotemporal transferability of statistical disease models.