Outcome Statement

Many viral respiratory diseases, including several caused by endemic human coronaviruses, possess seasonal prevalence peaks and other environmental or meteorological sensitivities. It is thus inferred that SARS-CoV-2 transmission and/or the severity of COVID-19, is also likely to be influenced by CME factors, such as temperature, humidity, solar radiation, PM2.5, and ground level ozone. These factors could influence where and when resurgences of the disease will occur, and how severe they may be. Therefore, it is important to understand the strength of evidence regarding environmental signals which may be helpful to predict the disease dynamics and communicate accurately science-based information to inform interventions such as vaccine campaigns and social distancing regulations. The virtual symposium provided an opportunity to review the global state of knowledge to date, discuss potential applications, and identify additional research and communication needs.

The following key messages were observed from contributions of leading experts and the studies presented and discussed at the symposium: 

 

1. Current peer-reviewed publications on the SARS-CoV-2 virus and the COVID-19 disease do not show a robust and consistent response to temperature, humidity, wind, solar radiation, nor other proposed meteorological and environmental drivers. Some evidence exists suggests that regulated indoor environmental conditions, in concert with behavioural factors, indirectly modulates localized spread of the virus. More research is needed on which climatic variables are most critical for understanding the likelihood of their influence and for disease risk reduction.

2. Evidence does indicate population exposure to air pollution, in the form of fine particulate matter, affects the severity of COVID-19 symptoms. This information should be considered when assessing and responding to patterns of COVID-19 vulnerability. Impacts of other air quality parameters are less clear, and the role of air quality in transmission rates is still under investigation.

3. The seasonality of COVID-19 has yet to be established as seasonal signals are difficult to distinguish at this early phase in the pandemic. Experience from other respiratory viruses suggests that a seasonal signal might emerge later as the disease becomes endemic.

4. COVID-19 exemplifies the importance to recognize human-environment interactions and disease prevention. SARS-COV-2 resulted from a zoonotic spillover event, whereby, the pathogen transferred from wildlife to humans. Human wildlife interactions increase zoonotic disease risk, as a result of human incursion into wildlands, and wildlife displacement to urban settings due to habitat destruction.

Interdisciplinary collaborations can significantly improve our understanding of major current and historical disease spillovers; as well as how CME factors contribute to the spread of infectious diseases and the emergence of new ones.

5. Learnings from other climate sensitive diseases should be applied to potential CME informed applications for COVID-19. This includes the need for strong transdisciplinary collaboration; communicating environmentally informed disease risk monitoring and early warning within a broader explanation of climate and environmental predictability and uncertainties; rigorous application of analytical methods; consistent and transparent data collection for assessing the influence of CME factors; and regular assessment of emerging knowledge. These elements are important for the appropriate identification of risk factors and potential risk mitigation actions, and the credibility of related predictive systems.

6. Understanding decision maker’s needs for timely and relevant information is critical for researchers to select the most appropriate applications of CME data, models, and forecasts to inform decision-making. Clear communication of confidence levels and uncertainty is essential for appropriate use of CME-informed epidemiological information. Diverse communication channel can help reach unique target audiences.

7. Current experimental CME-informed COVID-19 forecasts must be interpreted with extreme caution since it has not yet been possible to confirm the predictive power of CME variables for SARS-COV-2 transmission in a robust manner.

1. Global interdisciplinary research efforts should continue to explore the interactions of COVID-19 and CME factors, notably to discern the causal mechanisms through which CME factors may influence the transmission of SARS-CoV-2 and the severity of COVID-19. Carefully managed and coordinated interdisciplinary studies are required across localities, along with regular literature reviews.
2. To improve research outcomes, efforts are needed to encourage the integration of molecular, behavioral, and CME information and to promote a culture of open data sharing and scientific collaboration. Notably, interdisciplinary data collection and sharing mechanisms that facilitate access to aggregated confounding and behavioral data can improve intercomparison studies.
3. To improve research quality, replicability, and comparisons, recommendations and guidance providing minimum standards and good practice in CME informed disease modeling should be developed and promoted widely amongst researchers, donors, and publishers.
4. Decision-makers should be attentive to not depend on pre-reviewed papers or findings of single studies. All studies should be communicated carefully and in context, to avoid misinterpretation and misuse of information.
5. The World Meteorological Organization Research Board Task Team on COVID-19 and CME factors should consider the outcomes of this event to identify research priorities, further monitor scientific progress, and guide good practices for operational CME informed disease forecasting and information services.
6. Steps should be taken to inform and communicate research needs and priorities with key stakeholders, including research donors and the World Health Organization.