Little is known about how conspiracy beliefs and health responses are interrelated over time during the course of the coronavirus disease 2019 (Covid-19) pandemic. This longitudinal study tested two contrasting, but not mutually exclusive, hypotheses through cross-lagged modeling. First, based on the consequential nature of conspiracy beliefs, we hypothesize that conspiracy beliefs predict an increase in detrimental health responses over time. Second, as people may rationalize their behavior through conspiracy beliefs, we hypothesize that detrimental health responses predict increased conspiracy beliefs over time.

We measured conspiracy beliefs and several health-related responses (i.e. physical distancing, support for lockdown policy, and the perception of the coronavirus as dangerous) at three phases of the pandemic in the Netherlands (N = 4913): During the first lockdown (Wave 1: April 2020), after the first lockdown (Wave 2: June 2020), and during the second lockdown (Wave 3: December 2020).

For physical distancing and perceived danger, the overall cross-lagged effects supported both hypotheses, although the standardized effects were larger for the effects of conspiracy beliefs on these health responses than vice versa. The within-person change results only supported an effect of conspiracy beliefs on these health responses, depending on the phase of the pandemic. Furthermore, an overall cross-lagged effect of conspiracy beliefs on reduced support for lockdown policy emerged from Wave 2 to 3.

The results provide stronger support for the hypothesis that conspiracy beliefs predict health responses over time than for the hypothesis that health responses predict conspiracy beliefs over time.

During the first wave of the COVID-19 pandemic, distancing measures were enforced to reduce virus spread, which likely had an impact on the overall mental health of the population.

To investigate the prevalence of mental health outcomes (depression, anxiety and insomnia), and associated risk factors, during a physical distancing period imposed in the first wave of COVID-19.

During the first month of Portugal's state of emergency, an online survey was created and disseminated through social media channels. Sociodemographic and clinical variables were assessed via self-reported questionnaires. Univariate linear regressions were used to identify associations between the collected variables and mental health outcomes. Multivariate regression analyses were performed to identify independent risk factors for clinical outcomes, with adjustment for potential confounders.

We analysed data from 1626 participants: a significant proportion showed depression (30.2%), anxiety (53.1%) and insomnia (36.3%) symptoms. Multivariate regression models showed that being male and working from home were protective for all mental health outcomes analysed, whereas the perception of infection, being under psychiatric care and taking medication were risk factors (P < 0.05). Days in isolation and being unemployed were risk factors for depression and insomnia (P < 0.05). Younger age and being a student were risk factors for depression, whereas being a healthcare professional was protective (P < 0.05). Indirect contact with COVID-19 was a risk factor for anxiety (P < 0.05).

COVID-19-related distancing measures were associated with high levels of adverse mental health symptoms. Several risk factors were associated with these symptoms, which highlight the importance of identifying vulnerable groups during physical distancing periods.

No significant relationships.

This article investigates how a Chinese local government responded to the ongoing coronavirus disease 2019 (COVID-19) outbreak, and the lessons can be valuable for the ongoing response efforts worldwide.

This case study used primarily participant observations and interviews with stakeholders.

We find that nonpharmaceutical interventions, especially the physical distancing measures, are the primary tools used to contain the spread of the virus, and these actions keep changing to adapt to the situation of the local cases and the directions from the central government. Medical countermeasures, maintenance of essential public services, and effective public communications tactics are important allies of the strict physical distancing measures, which can enforce the public’s compliance.

Local governments are the frontlines of emergency response. Both regulated policies (eg, physical distancing) and supportive services (eg, medical and essential living support) are necessary to the success of public health emergency response.