Healthcare in a Changing Climate 2025

A. Impact triggered by climate change The quantified impact of climate change on human health from the Forum’s Quantifying the Impact of Climate Change on Human Health served as a starting point for assessing preventable health and economic impacts at a disease level for each of the six regions as per the WMO’s classification: Africa, Asia, South America, South-West Pacific, Europe and North America, Central America and the Caribbean. For example, malaria is expected to cause an additional health impact of 399 million DALYs, productivity losses of $926 billion, treatment costs of $31 billion and 8 million additional deaths in Africa by 2050. B. Share of health and economic impacts that specific unmet need could reduce This coefficient represents the portion of the health and economic outcome that could be prevented if the unmet needs were fully addressed. This may include the share of patients with treatment- resistant diseases, undiagnosed or misdiagnosed cases, or incidences occurring in areas where vaccination is justified. For example, developing a treatment for multi-drug-resistant malaria could address from 35% to 46% of cases where current treatments fail to eliminate the malaria parasite, depending on the region. C. Share of health and economic impacts addressable by life sciences sector This coefficient is based on four parameters: 1) Required R&D time, 2) Innovation adoption rate, 3) Access to healthcare and technology, and 4) Health and economic impact trajectory: 1) Required R&D time – defined as the number of years necessary to develop a new vaccine, medtech device, drug or digital therapeutic app. R&D time was estimated by considering an accelerated development pathway, reflecting the urgency recognized by the life sciences community and regulatory bodies. For every intervention type across vaccines, diagnostics, treatment and digital therapeutics, the average development time for new solutions was calculated, incorporating historical benchmarks alongside accelerated timelines observed during the COVID-19 pandemic. –Vaccines: R&D timeline of six years was considered for all innovative vaccines, as an average between the historical R&D timeline (10 years) and accelerated timeline observed during the COVID-19 pandemic (one year). –Diagnostics: R&D timeline of three years was considered for all innovative diagnostic kits, as an average between historical R&D timeline for medical devices (five years) and accelerated timeline observed during the COVID-19 pandemic (three months for diagnostic tests). –Drugs: R&D timeline of six years was considered for all innovative drugs, as an average between historical R&D timeline (10.5 years) and accelerated timeline observed during the COVID-19 pandemic (one year for new vaccine development). –Digital therapeutics: R&D timeline of two years was considered for all innovative digital therapeutics, based on the historical R&D timeline for healthcare app (18 months development and six months for approval following Premarket Notification 510(k) procedure). 2) Innovation adoption rate – defined as the share of disease incidences that gets treated by the new intervention each year upon completion of the R&D process. This captures both physician adoption and patient uptake rates. It is eventually capped by the degree of access to healthcare and technology. The adoption rate was assessed based on historical adoption. –Vaccines: The adoption rate of the COVID-19 vaccine was considered as a benchmark, reaching 10% of global population in the launch year, 49% two years after launch, 63% three years after launch and 65% four years after launch. The same timeline was assumed for all innovative vaccines. From year five after launch onwards, an additional 2% growth of adoption rate was assumed, similar to the incremental growth of adoption rate in year four after COVID-19 vaccine launch (increase from 63% to 65%). –Medical technology diagnostic devices: The adoption rate of malaria rapid diagnostic tests (RDTs) in Africa was used as a benchmark. Malaria RDTs are not a novel solution; however from 2010-2019 a major effort was made to widen their availability, resulting in an increase in usage from 36% to 87%. As such, an average 5% annual increase in adoption rate was assumed for all innovative diagnostic kits. –New treatments: The adoption rate of new drugs by physicians was considered as a benchmark. Studies for innovative cardiovascular drugs have demonstrated that 35% of physicians start prescribing the new drug in the first 18 months after it is introduced into the market. As such, an average 21% annual increase in adoption rate for each consecutive year after drug launch was assumed for all innovative treatments. 3) Access to healthcare and technology – defined as the maximum share of annual disease incidences which could be reached by the new intervention by 2050. For most interventions, the innovation adoption rate is eventually limited by the level of healthcare access in the region. Healthcare in a Changing Climate: Investing in Resilient Solutions 36