Objectives: Some people do not fully recover from an acute viral infection and experience persistent symptoms or incomplete recovery for months or even years. This is not unique to the SARS-CoV-2 virus and history shows that post-viral conditions like post COVID-19 condition, also referred to as Long Covid, are not new. In particular, during and after pandemics caused by respiratory viruses in which large parts of the population were infected or exposed, professional and public attention was increased, not least because of the large number of people affected. Methods: Given the current relevance of the topic, this article aims to narratively review and summarize the literature on post-viral symptoms during past pandemics and to supplement and illustrate it with Swiss examples from the pandemics of 1890, 1918-1920 and later. Results: Post-viral diseases were an increasingly emphasised health topic during and after past pandemics triggered by respiratory infections over the last 150 years. Conclusion: In the next pandemic, it should not be surprising that post-viral conditions will again play a role, and pandemic plans should reflect this.

In Alaska, the 1918-20 influenza pandemic was devastating, with mortality rates up to 90% of the population, while in other arctic regions in northern Sweden and Norway mortality was considerably lower. We investigated the timing and age-patterns in excess mortality in Greenland during the period 1918-21 and compare these to other epidemics and the 1889-92 pandemic. We accessed the Greenlandic National Archives and transcribed all deaths from 1880 to 1921 by age, geography, and cause of death. We estimated monthly excess mortality and studied the spatial-temporal patterns of the pandemics and compared them to other mortality crises in the 40-year period. The 1918-21 influenza pandemic arrived in Greenland in the summer of 1919, one year delayed due to ship traffic interruptions during the winter months. We found that 5.2% of the Greenland population died of the pandemic with substantial variability between counties (range, 0.1% to 11%). We did not see the typical pandemic age-pattern of high young-adult mortality, possibly due to high baseline mortality in this age-group or remoteness. However, despite substantial mortality, the mortality impact was not standing out relative to other mortality crises, or of similar devastation reported in Alaskan populations.

BACKGROUND: We describe how rates of two frequently occurring notifiable diseases-diphtheria and scarlet fever-varied between regions of The Netherlands in the early twentieth century, and identify potential factors underlying this variation.
METHODS: Digitized weekly mandatory notification data for 1905-1925, municipality level, were aggregated into 27 \'spatial units\' defined by unique combinations of province and population density category (high: more than 4500; mid : 1250-4500; low: less than 1250 inhabitants km-2). Generalized additive regression models were fitted to estimate the associations between notification rates and population density, infant mortality rate and household income, while adjusting for temporal trends per spatial unit.
RESULTS: Annual per capita notification rates for both diphtheria and scarlet fever tended to rise from the beginning of the period 1905-1925 until peaking around 1918/1919. Adjusted diphtheria notification rates were higher for high- and mid- compared with low-density municipalities (by 71.6 cases per 100 000, 95% confidence interval (CI) : 52.7-90.5; 39.0/100 k, 95% CI : 24.7-53.3, respectively). Scarlet fever showed similar associations with population density (35.7 cases per 100 000, 95% CI : 9.4-62.0; 21.4/100 k, 95% CI: 1.5-41.3).
CONCLUSIONS: There was considerable spatial variation in notification rates for both diseases in early twentieth century Netherlands, which could partly be explained by factors capturing variation in living conditions and socio-economic circumstances. These findings aid understanding of contemporary respiratory infection transmission.

Undifferentiated febrile diseases (e.g., Mossman fever) from northern Queensland were eventually partially attributed to mite-transmitted rickettsial infections known as scrub typhus or tsutsugamushi fever. Scrub typhus became a major medical threat to military operations in Papua New Guinea during the Second World War and killed more Australian soldiers than malaria in the pre-antibiotic era. Further investigations showed scrub typhus to be an occupational disease of rural workers in north Queensland especially around Cairns and Innisfail. Occasional small epidemics of scrub typhus still occur during military exercises in Queensland, but as scrub typhus is not a reportable disease, its presence in the civilian community is largely unknown. Increased use of serological testing in patients with fever and rash illnesses after exposure in northern Queensland is likely to show that scrub typhus is a modern infection that remains treatable with antibiotics once it is identified.

The perfect storm model that was elaborated for the HIV-1M pandemic has also been used to explain the emergence of HIV-2, a second human immunodeficiency virus-acquired immunodeficiency syndrome (HIV-AIDS) that became an epidemic in Guinea-Bissau, West Africa. The use of this model creates epidemiological generalizations, ecological oversimplifications and historical misunderstandings as its assumptions-an urban center with explosive population growth, a high level of commercial sex and a surge in STDs, a network of mechanical transport and country-wide, en masse mobile campaigns-are absent from the historical record. This model fails to explain how the HIV-2 epidemic actually came about. This is the first study to conduct an exhaustive examination of sociohistorical contextual developments and align them with environmental, virological and epidemiological data. The interdisciplinary dialogue indicates that the emergence of the HIV-2 epidemic piggybacked on local sociopolitical transformations. The war\'s indirect effects on ecological relations, mobility and sociability were acute in rural areas and are a key to the HIV-2 epidemic. This setting had the natural host of the virus, the population numbers, the mobility trends and the use of technology on a scale needed to foster viral adaptation and amplification. The present analysis suggests new reflections on the processes of zoonotic spillovers and disease emergence.

The overall suicide rate in China has dropped substantially since the 1990s, but a slowdown in the decrease and even a reversing trend was observed in specific groups in recent years. This study aims to investigate the latest suicide risk in mainland China by using the age-period-cohort (APC) analysis.
This population-based multiyear cross-sectional study included Chinese ages 10 to 84 years using data from the China Health Statistical Yearbook (2005-2020). Data were analyzed by the APC analysis and intrinsic estimator (IE) technique.
The data satisfactorily fit the constructed APC models. The cohort effect indicated a high risk of suicide among people birth in 1920-1944 and a sharp decline in the 1945-1979 cohort. The lowest risk occurred in the 1980-1994 cohort before a sharp increase in generation Z (birth years in 1995-2009). The period effect showed a declining trend since 2004. The age effect indicated that the suicide risk increased over time, except for a gradual decline from age 35 to 49. The suicide risk increased greatly in adolescents and reached the highest among the elderly.
The aggregated population-level data and the non-identifiability of the APC model could result in bias in the accuracy of results in this study.
This study successfully updated the Chinese suicide risk from the age, period and cohort perspective using the latest available data (2004-2019). The findings enhance the understanding of suicide epidemiology and provide evidence supporting policies and strategies at the macro-level for suicide prevention and management. Immediate action is needed to focus on a national suicide prevention strategy that targets generation Z, adolescents and the elderly which will require a collaborative effort by government officials, public/community health planners and health care agencies.

Historical death registration was conducted primarily to assess the presence of plague. The Liber Mortuorum of Milan was one of Europe\'s first registers with many socio-demographical details. In this work, we consider 1480 to make spatial and temporal analyses of the event of death to find possible explanations about the events\' distribution and the events\' trend over time. The spatial analyses involved Moran\'s I, the LISA, and the heatmaps; the temporal analysis applied the Durbin-Watson test. All the analyses were conducted separately on all subjects (1813), children (765), and adults (1046). Contrade (districts) were considered for spatial analysis. Moran\'s I and the Durbin Watson test were significant on all subjects and children\'s analyses, and the LISA showed the same results for those groups. Children may significantly impact the distribution of death and the trend over time. At least half of the children were 0 years old, and survival in the very first childhood period was closely linked to the family, so that it could be a proxy of the conditions of an area.

Pandemic diseases such as plague have produced a vast amount of literature providing information about the spatiotemporal extent, transmission, or countermeasures. However, the manual extraction of such information from running text is a tedious process, and much of this information remains locked into a narrative format. Natural Language processing (NLP) is a promising tool for the automated extraction of epidemiological data, and can facilitate the establishment of datasets. In this paper, we explore the utility of NLP to assist in the creation of a plague outbreak dataset. We produced a gold standard list of toponyms by manual annotation of a German plague treatise published by Sticker in 1908. We investigated the performance of five pre-trained NLP libraries (Google, Stanford CoreNLP, spaCy, germaNER and Geoparser) for the automated extraction of location data compared to the gold standard. Of all tested algorithms, spaCy performed best (sensitivity 0.92, F1 score 0.83), followed closely by Stanford CoreNLP (sensitivity 0.81, F1 score 0.87). Google NLP had a slightly lower performance (F1 score 0.72, sensitivity 0.78). Geoparser and germaNER had a poor sensitivity (0.41 and 0.61). We then evaluated how well automated geocoding services such as Google geocoding, Geonames and Geoparser located these outbreaks correctly. All geocoding services performed poorly - particularly for historical regions - and returned the correct GIS information only in 60.4%, 52.7% and 33.8% of all cases. Finally, we compared our newly digitized plague dataset to a re-digitized version of the plague treatise by Biraben and provide an update of the spatio-temporal extent of the second pandemic plague outbreaks. We conclude that NLP tools have their limitations, but they are potentially useful to accelerate the collection of data and the generation of a global plague outbreak database.

Singapore surrendered to the Japanese invasion in February 1942 after its water supply collapsed. At the suggestion of the colonial medical authorities, an emergency typhoid immunisation campaign was then begun using locally manufactured vaccine from extemporary materials; within 3 months, >600 000 had been immunised. Comparison with prewar statistics suggests that a postsurrender typhoid fever epidemic was prevented despite an increase in other enteric infections. Public health crises with disrupted supply chains may make locally manufactured vaccines of increasing importance in the future.

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