From respiratory diseases to nervous system disorders: Unraveling the certified causes of influenza-associated deaths in Poland from 2000 to 2019

Respiratory Diagnoses Year-Round: Unraveling the Multifaceted Pediatric Infection Cycles

OBJECTIVE

The aim of the study is to analyze the annual cycle of pediatric medically attended respiratory illnesses.

STUDY DESIGN

Data on 141 million pediatric respiratory visits from the years 2010-2019 were obtained from the Polish National Healthcare Fund. To identify underlying patterns and trends within the aggregated data, techniques like seasonal-trend decomposition using LOESS (STL) and principal component analysis (PCA) were applied.

RESULTS

A strongly recurring pattern was observed. Following the annual minimum in late summer, there was a sudden surge in upper respiratory infections in early September. Subsequently, overall visits declined gradually, while the share of lower respiratory infections increased, particularly during the influenza peaks from January to March. Afterwards, visits declined steadily, with an additional peak of tonsillopharyngitis noted in midsummer. Dimensionality reduction of diagnoses implied the existence of two major groups of co-occurring diagnoses, the proportions of which change over the year: one smaller but more severe, peaking during the influenza season, and the second dominating with lower severity. Age differences in diagnoses were observed, with babies showing upper respiratory infections likely diagnosed with the common cold rather than a more specific upper respiratory infection.

CONCLUSION

While enhancing surveillance strategies is indeed a desirable long-term goal, it is worth noting that despite the variability observed in the onset of the influenza season, the infection cycles generally follow a relatively fixed pattern. This consistency provides a foundation for effective planning and underscores the potential for proactive measures to mitigate the impact of seasonal outbreaks.

Beyond the sine wave: unveiling climate-driven baseline mortality cycles

The relationship between temperature and mortality is well-established, with higher mortality rates occurring in moderate climates during winter. Studies on COVID-19 and influenza-related excess deaths often assume a sine-like wave pattern for baseline mortality. This study aims to assess the accuracy of this approximation in capturing the observed mortality pattern and explore its linkage with climate. Weekly mortality data from European regions (2000-2019) were modeled using the seasonal-trend decomposition procedure based on Loess. Cycles were grouped into clusters, and underlying trends were extracted using principal component analysis. Generalized linear models assuming a sine-like pattern were used to test predictive value. Cluster analysis divided the regional cycles approximately into continental and temperate climate regions, further subdivided into oceanic and Mediterranean. While the continental region exhibited a sine-like mortality pattern, it displayed modest deviations that compounded further south. The period of elevated winter mortality became shorter but more intense, while decreased summer mortality became more pronounced yet delayed. This study improves weekly estimations of excess mortality models by providing enhanced baselines. The deviation from the sine-like approximation mirrors the idealized outbreak pattern from epidemiological models with sharper surges and more gradual declines. The results point to winter infections, impacted by acquired immunity and weather conditions, as the primary drivers of fluctuations in mortality. In warmer regions, there is an apparent shift toward a lower number of overall infections within a compressed time span.

Exploring the paradoxical nature of cold temperature mortality in Europe

While low winter temperatures are associated with increased mortality, this phenomenon has been suggested to be most severe in regions with seemingly mild winters. The study aimed to establish a temperature-based formula that could elucidate the previously ambiguous regional differences in vulnerability to low temperature. European weekly mortality data (2000-2019) were matched with meteorological data to determine for each region vulnerability to temperature decrease and the optimal temperature with lowest mortality. Regression models were developed to generalize and explain these findings considering regional temperature characteristics. Optimal temperature could be predicted based on local average summer temperature (R2 = 85.6%). Regional vulnerability to temperature decrease could be explained by combination of winter and summer temperatures (R2 = 86.1%). Regions with warm winters and cold summers showed the highest vulnerability to decrease of temperature during winter. Contrary to theories about economic disparities Eastern Europe exhibited resistance comparable to Scandinavia. The southern edges of Europe demonstrated serious low temperature vulnerability to decreased temperatures, even if temperature was relatively high around 20 °C. This suggests that the observed connection primarily reflects the modulation of the length of respiratory virus infection seasons by climate conditions, counterbalanced by varying levels of acquired immunity and the presence of heatwaves eliminating the most frail individuals. Thus, relatively low vulnerability and a flat mortality cycle in countries with harsh climates paradoxically imply the presence of threats throughout the whole year.