Dückers, Michel

De coronacrisis en de gevolgen die deze op de gezondheid van de Nederlandse bevolking heeft gaan de normale regionale onderzoeksaanpak te boven. Daarom heeft het Netwerk GOR-COVID- 19 – dat bestaat uit GGD GHOR Nederland (namens de GGD’en), RIVM, Nivel en ARQ Nationaal Psychotrauma Centrum – het initiatief genomen voor een landelijk onderzoeksprogramma om de impact van de coronapandemie op de mentale en fysieke gezondheid van de Nederlandse bevolking op lange termijn te monitoren: de integrale Gezondheidsmonitor COVID-19.

Disasters and humanitarian crises threaten the health and wellbeing of people across the world, especially in more vulnerable regions. Many efforts are made to ensure that public health interventions, including mental health and psychosocial support (MHPSS), are based on the best available evidence.

In the course of the COVID-19 pandemic, it has become clear that primary healthcare systems play a critical role in clinical care, such as patient screening, triage, physical and psychological support and also in promoting good community advice and awareness in coordination with secondary healthcare and preventive care. Because of the role of social and environmental factors in COVID-19 transmission and burden of disease, it is essential to ensure that there is adequate coordination of population-based health services and public health interventions.

Background: During times of crisis, mayors may play an important role as public leaders and providers of social support to affected residents. However, empirical studies have not yet been conducted among the involved mayors about the support they provide and the factors associated with it.

Objective: The aim is to examine the support the mayors provided to the affected residents during crises and to test the possible determinants of this support.

Background: Little is known about the public health impact of chronic exposure to physical and social stressors in the human environment. Objective of this study was to investigate the immediate and long-term health effects of living in an environment with gas-mining induced earthquakes and related stressors in the Netherlands.

IMPORTANCE Conducted electrical weapons (CEWs) are used broadly as a less-lethal force option for police officers. However, there is no clear picture of the possible health risks in humans on the basis of rigorously assessed scientific evidence from the international peer-reviewed literature.

OBJECTIVE To synthesize and systematically evaluate the strength of published evidence for an association between exposure to different models of CEWs and adverse acute as well as chronic conditions.
 

In the current COVID-19 crisis, global and national public health authorities and organisations are searching their toolbox of methods and approaches to communicate to and connect with populations. As with HIV/AIDS or Ebola Virus Disease (EVD) in West Africa, it became quickly apparent that the participation of those most affected by the disease, and communities in general, play a central role in understanding how to best shape and implement response efforts .

Op 22 juli 2019 kopte het Algemeen Dagblad: ‘Wie durft nog zorgeloos door het bos te banjeren?’ Naast de teek moesten mensen nu ook voorzichtig zijn voor de reuzenteek, het ‘dracula’ draaigatje (een mier), de rode vuurmier en de wolf, die alleen bij drs. P ook mensen eet. Ook andere invasieve exoten roepen vrees op, zoals de gewone Aziatische hoornaar (‘killer bee’), de Aziatische reuzenhoornaar (‘murder hornet’), de tijgermug, de wasbeer en de voor mensen met hooikoorts zeer irritante en lastige Alsemambrosia-plant.

Introduction:
Societies invest substantial amounts of resources on disaster preparedness of hospitals. However, the concept is not clearly defined nor operationalized in the international literature.

Aim:

This review aims to systematically assess definitions and operationalizations of disaster preparedness in hospitals, and to develop an all-encompassing model, incorporating different perspectives on the subject.

Methods:

Background: Suicidal behaviour is difficult to detect in the general practice. Machine learning (ML) algorithms using routinely collected data might support General Practitioners (GPs) in the detection of suicidal behaviour. In this paper, we applied machine learning techniques to support GPs recognizing suicidal behaviour in primary care patients using routinely collected general practice data.