Fig. 1. Visualization of the Horizon Scanning (HS) methodology adopted in the current study. The process involves four stages, namely, lessons collection; filtration; categorization, merging and validation; and evaluation.
2.1.1 Stage 1 - Lessons collection
In the current research, we scanned two main sources of information regarding transferable lessons from COVID-19 to climate change. These sources are published peer-reviewed articles and individuals from 49 different countries, including experts and non-experts. For the non-experts, we asked the first survey participants to confirm their willingness to participate in the second survey. For the participant selection in the expert survey, besides a number of authors of the 90 deemed pertinent articles out of the considered literature (108 peer-reviewed articles), experts from academia who contributed to research concerning COVID-19 and climate change were selected.
To collect and rank lessons from individuals, we created two online surveys (See the Supplementary Information file; Section SI.1). The first survey was designed to collect COVID-19 lessons from all participants. In order to increase the pool of participants and to get insights from different countries, we reached out to participants by creating our website, as well as social media, and LinkedIn pages expanding on the project goals and spreading the word. Moreover, all our surveys were available in four languages, i.e., English, German, Spanish, and Arabic. For the online surveys, the soSci-Survey online platform (https://www.soscisurvey.de/) was used. Online surveys allowed for a diversification of sources and inclusion of lived experiences of people directly affected by different policy measures undertaken by various countries and regions. For all surveys, the participants were informed about the purpose of the research and the use of data and asked about their voluntary participation. The first survey was published in May 2021. The participants were asked, using a 5-point Likert-scale, how they would rate their level of expertise regarding the issues of COVID-19 and climate change, and how concerned they are about them.
• “How would you rate your level of expertise on COVID-19? How would you rate your level of expertise on climate change?” • “How concerned are you about COVID-19? How concerned are you about climate change?” Then the participants were asked two open questions: • “What are your lessons learned from the COVID-19 pandemic in general?” • “What are your lessons learned from the COVID-19 pandemic related to climate change?”
Finally, the socio-demographic data of the participants were requested in order to characterize the sample. The entire survey was anonymous, and the participants have been assigned special identification numbers to replace their biometric information. The participants in the first survey were 220, leading to a total number of 69 unique relevant lessons, containing a range of similar lessons that were merged. These lessons were assigned to nine thematic areas (see section 2.1.3). The lessons collected were then turned into the second public survey, the survey was published in July 2021 with the help of the Sosci-survey platform. First, the participants had to rank the thematic areas according to their importance for climate change or COVID-19:
1. “In relation to the current COVID-19 pandemic, how important do you think the following areas are for finding a solution?” 2. “Concerning the global issue of Climate Change, how important do you think the following areas are for finding suitable solutions?”
These questions were asked through a 5 level Likert-scale from 1 “not important” to 5 “very important”.
To better assess the sample, all study participants were asked to indicate their level of expertise regarding how familiar they are with climate change and COVID-19, using a five-point Likert scale, where 1 represents “not an expert” and 5 “expert”. The lessons that ranked highest on these criteria were considered in the further process.
In the second survey, the most relevant lessons learned were listed, using our developed filtering procedure. Subsequently, participants were asked to judge the relevance of the lessons learned on a seven-point-Likert-Scale, with 1 “strongly disagree” to 7 “strongly agree”. The Likert-Scale was increased from 5 to 7 with the aim to point out a gradient and more nuanced differences in responses. The same survey was distributed to the experts’ group at the same time. In the second part of this survey, participants ranked lessons according to their importance. For this, a seven-point Likert scale form was used. Through this, the most important lessons for the general public could be identified. Finally, socio-demographic data was requested, and information about the use of data and voluntary participation were provided.
To allow for collecting interdisciplinary lessons from COVID-19 relevant to climate change, we reviewed 108 published articles with themes of COVID-19 and climate change. These articles have been collected and screened for relevance, based on whether insights from COVID-19 were applicable to climate change. Refer to the Supplementary Information file for a list of the 108 reviewed literature (SI.2). Out of 108 peer-reviewed articles, 90 were deemed pertinent and contained lessons from COVID-19 relevant to climate change. From the relevant literature, a total of 362 lessons were collected.
2.1.2 Stage 2 - Filtration
For lesson filtration, we adopted the common criteria described by Hines et al. (2019) after being customized to fit the specific purpose of the current research. We developed a quantitative matrix to evaluate all the collected lessons based on these criteria (Table 1), with a 0 score (red) meaning criteria not applicable, 1 (yellow) less applicable, and 2 (green) highly applicable.
Table 1. The filtration methodology, including criteria used for this procedure.