An outbreak of Legionnaires' disease linked to a municipal and industrial wastewater treatment plant, The Netherlands, September-October 2022.

Wastewater treatment plants (WWTPs) are increasingly identified as Legionnaires' disease (LD) sources. An outbreak investigation was initiated following five LD cases reported in September 2022 in Houten, the Netherlands. Case identification was based on the European LD case definition, with symptom onset from 1 September 2022, residence in or within 5 km of Houten, or visit to Houten within the incubation period, without other likely sources. We sampled potential sources and genotyped environmental and clinical isolates. We identified 15 LD cases with onset between 13 September and 23 October 2022. A spatial source identification and wind direction model suggested an industrial (iWWTP) and a municipal WWTP (mWWTP) as potential sources, with the first discharging water into the latter. Both tested positive for Legionella pneumophila serogroups 1 and 6 with multiple sequence types (ST). We detected L. pneumophila sg1 ST42 in the mWWTP, matching with one of three available clinical isolates. Following control measures at the WWTPs, no further cases were observed. This outbreak underlines that municipal and industrial WWTPs can play an important role in community LD cases and outbreaks, especially those with favourable conditions for Legionella growth and dissemination, or even non-favourable conditions for growth but with the influx of contaminated water.

[Climate change and infectious diseases]. / Klimaatverandering en infectieziekten wereldwijd.

Climate change can contribute to a global increase in the burden of infectious diseases. Both the number of geographical areas as well as the number of yearly days that are suitable for transmission of certain infectious diseases can increase due to global warming. At the same time, increased 'suitability' does not always lead to a factual increase in disease burden and economic development and public health measures have resulted in marked reductions in the burden of several important infectious diseases in recent years. The net effect of global environmental change on infectious disease burden will be determined by a multitude of factors, including unpredictable outbreaks of pathogens and the extent to which public health programs can effectively function and adjust to changing health risks.

An exploration of the disease burden due to Cryptosporidium in consumed surface water for sub-Saharan Africa.

The protozoan pathogen Cryptosporidium is an important cause of diarrhoeal disease, but in many contexts its burden remains uncertain. The Global Waterborne Pathogen model for Cryptosporidium (GloWPa-Crypto) predicts oocyst concentrations in surface water at 0.5 by 0.5° (longitude by latitude) resolution, allowing us to assess the burden specifically associated with the consumption of contaminated surface water at a large scale. In this study, data produced by the GloWPa-Crypto model were used in a quantitative microbial risk assessment (QMRA) for sub-Saharan Africa, one of the regions most severely affected by diarrhoeal disease. We first estimated the number of people consuming surface water in this region and assessed both direct consumption and consumption from a piped (treated) supply. The disease burden was expressed in disability adjusted life years (DALYs). We estimate an annual number of 4.3 × 107 (95% uncertainty interval [UI] 7.4 × 106-5.4 × 107) cases which represent 1.6 × 106 (95% UI 3.2 × 105-2.3 × 106) DALYs. Relative disease burden (DALYs per 100,000 persons) varies widely, ranging between 1.3 (95% UI 0.1-5.7) for Senegal and 1.0 × 103 (95% UI 4.2 × 102-1.4 × 103) for Eswatini. Countries that carry the highest relative disease burden are primarily located in south and south-east sub-Saharan Africa and are characterised by a relatively high HIV/AIDS prevalence. Direct surface water consumption accounts for the vast majority of cases, but the results also point towards the importance of stable drinking water treatment performance. This is, to our knowledge, the first study to utilise modelled data on pathogen concentrations in a large scale QMRA. It demonstrates the potential value of such data in epidemiological research, particularly regarding disease aetiology.