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.