Advancing insights into methods for studying environment–health relationships: A multidisciplinary approach to understanding Legionnaires’ disease

Impacts of weather and air pollution on Legionnaires' disease in Switzerland: A national case-crossover study

BACKGROUND

The number of reported cases of Legionnaires' disease (LD) has risen markedly in Switzerland (6.5/100,000 inhabitants in 2021) and abroad over the last decade. Legionella, the causative agent of LD, are ubiquitous in the environment. Therefore, environmental changes can affect the incidence of LD, for example by increasing bacterial concentrations in the environment or by facilitating transmission.

OBJECTIVES

The aim of this study is to understand the environmental determinants, in particular weather conditions, for the regional and seasonal distribution of LD in Switzerland.

METHODS

We conducted a series of analyses based on the Swiss LD notification data from 2017 to 2021. First, we used a descriptive and hotspot analysis to map LD cases and identify regional clusters. Second, we applied an ecological model to identify environmental determinants on case frequency at the district level. Third, we applied a case-crossover design using distributed lag non-linear models to identify short-term associations between seven weather variables and LD occurrence. Lastly, we performed a sensitivity analysis for the case-crossover design including NO2 levels available for the year 2019.

RESULTS

Canton Ticino in southern Switzerland was identified as a hotspot in the cluster analysis, with a standardised notification rate of 14.3 cases/100,000 inhabitants (CI: 12.6, 16.0). The strongest association with LD frequency in the ecological model was found for large-scale factors such as weather and air pollution. The case-crossover study confirmed the strong association of elevated daily mean temperature (OR 2.83; CI: 1.70, 4.70) and mean daily vapour pressure (OR: 1.52, CI: 1.15, 2.01) 6-14 days before LD occurrence.

DISCUSSION

Our analyses showed an influence of weather with a specific temporal pattern before the onset of LD, which may provide insights into the effect mechanism. The relationship between air pollution and LD and the interplay with weather should be further investigated.

Confirmed and Potential Sources of Legionella Reviewed

Legionella bacteria are ubiquitous in natural matrices and man-made systems. However, it is not always clear if these reservoirs can act as source of infection resulting in cases of Legionnaires' disease. This review provides an overview of reservoirs of Legionella reported in the literature, other than drinking water distribution systems. Levels of evidence were developed to discriminate between potential and confirmed sources of Legionella. A total of 17 systems and matrices could be classified as confirmed sources of Legionella. Many other man-made systems or natural matrices were not classified as a confirmed source, since either no patients were linked to these reservoirs or the supporting evidence was weak. However, these systems or matrices could play an important role in the transmission of infectious Legionella bacteria; they might not yet be considered in source investigations, resulting in an underestimation of their importance. To optimize source investigations it is important to have knowledge about all the (potential) sources of Legionella. Further research is needed to unravel what the contribution is of each confirmed source, and possibly also potential sources, to the LD disease burden.

Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling

This study investigated the relationships between Legionnaires' disease (LD) incidence and weather in Glasgow, UK, by using advanced statistical methods. Using daily meteorological data and 78 LD cases with known exact date of onset, we fitted a series of Poisson log-linear regression models with explanatory variables for air temperature, relative humidity, wind speed and year, and sine-cosine terms for within-year seasonal variation. Our initial model showed an association between LD incidence and 2-day lagged humidity (positive, P = 0·0236) and wind speed (negative, P = 0·033). However, after adjusting for year-by-year and seasonal variation in cases there were no significant associations with weather. We also used normal linear models to assess the importance of short-term, unseasonable weather values. The most significant association was between LD incidence and air temperature residual lagged by 1 day prior to onset (P = 0·0014). The contextual role of unseasonably high air temperatures is worthy of further investigation. Our methods and results have further advanced understanding of the role which weather plays in risk of LD infection.

Methods and tools for geographical mapping and analysis in primary health care

AIM

The purpose of this paper is to review methods and tools for mapping, visualising and exploring geographic information to aid in primary health care (PHC) research and development.

BACKGROUND

Mapping and spatial analysis of indicators of locality health profiles and healthcare needs assessment are well-established facets of health services research and development. However, while there are a range of different methods and tools used for these purposes, non-specialists responsible for managing the use of such information systems may find knowing where to start and what can be done a relatively steep learning curve. In this review, health and sociodemographic datasets are used to illustrate some key methods, tools and organisational issues, and builds upon two recent reviews in this journal, respectively, focusing on geographic data sources and geographic concepts. Those familiar with mapping and spatial analysis should find this a useful review of current matters.

METHOD

A thematic review is presented with illustrative case studies relevant to PHC. It begins with a section on visualising and interpreting geographic information. This is followed by a section critiquing analytical methods. Consideration is given to software and deployment issues in a third section. Content is based on domain knowledge of the authors as a team of geographic information scientists and a public health practitioner working in tandem, with its scope restricted to routine applications of mapping and analysis. Advanced techniques such as spatio-temporal modelling are not considered, neither are methodological technicalities, although guidance on further reading is provided.

SUMMARY

Geographical perspectives are now playing a significant role in PHC delivery, and for those engaged in informatics and/or managing population-level care, understanding key geographic information systems methods and terminologies are important as is gaining greater familiarity with institutional aspects of implementation.

Characteristics and risk factors for typhoid fever after the tsunami, earthquake and under normal conditions in Indonesia

Background

Although typhoid transmitted by food and water is a common problem in daily life, its characteristics and risk factors may differ in disaster-affected areas, which reinforces the need for rapid public health intervention. Surveys were carried out post-tsunami in Banda Aceh, post-earthquake in Yogyakarta, and under normal conditions in Bandung, Indonesia. Logistic regression analysis was used to assess the risk factors with the dependent variable of typhoid fever, with or without complications.

Findings

Characteristic typhoid fever with complications was found in 5 patients (11.9%) affected by the tsunami in Aceh, 8 (20.5%) after the earthquake in Yogyakarta, and 13 (18.6%) in Bandung. After the tsunami in Aceh, clean water (OR = 0.05; 95%CI: 0.01-0.47) and drug availability (OR = 0.23; 95%CI: 0.02-2.43) are significant independent risk factors, while for the earthquake in Yogyakarta, contact with other typhoid patients (OR = 20.30; 95%CI: 1.93-213.02) and education (OR = 0.08; 95%CI: 0.01-0.98) were significant risk factors. Under normal conditions in Bandung, hand washing (OR = 0.07; 95%CI: 0.01-0.50) and education (OR = 0.08; 95%CI: 0.01-0.64) emerged as significant risk factors.

Conclusion

The change in risk factors for typhoid complication after the tsunami in Aceh and the earthquake in Yogyakarta emphasizes the need for rapid public health intervention in natural disasters in Indonesia.

Geographical variation of sporadic Legionnaires' disease analysed in a grid model

The aim was to analyse variation in incidence of sporadic Legionnaires' disease in a geographical information system in three time periods (1990–2005) by the application of a grid model and to assess the model's validity by analysing variation according to grid position. Coordinates of the addresses at time of disease of 606 confirmed cases with Legionnaires' disease were obtained. The incidence was calculated in cells of 10×10 km in 25 different grids superimposed on a map of Denmark. A 95% and 99% threshold was applied to identify cells with excess incidence representing potential clusters. Four cells had excess incidence in all three time periods. The analysis in 25 different grid positions indicated a low risk of overlooking cells with excess incidence in a random grid. The coefficient of variation ranged from 0·08 to 0·11 independent of the threshold. By application of a random grid model we demonstrated that it was possible to detect small areas with excess incidence that were not detected in the present surveillance system.

"To me it's just another tool to help understand the evidence": public health decision-makers' perceptions of the value of geographical information systems (GIS)

While geographical information systems (GIS) have applications in a range of diverse fields, they remain underused by decision-makers in health settings. Through analysis of data captured in semi-structured interviews, the paper explores four thematic areas (the ontological, power, functionality and collaboration discourses) to understand how GIS are perceived and valued by public health decision-makers. The findings suggest that although GIS are viewed as useful tools to inform decision-making, they are in no way a panacea for practice. Participants' concerns that GIS outputs can potentially be misinterpreted or used erroneously might partly explain resistance to their use. GIS are, therefore, likely to be most effective in decision-making when applied in a multi-disciplinary context to facilitate sharing of data, knowledge and expertise across the public health landscape.