The effects of war on Ukrainian research

Russia’s full-scale invasion of Ukraine on 24 February 2022 has caused massive civilian casualties, displacement, and infrastructure destruction. Around early 2023, approximately 18% of the population had taken shelter in Europe, with many relocating within Ukraine. The science sector has been heavily disrupted, with university closures or destruction and scientists changing careers or fleeing. Prior work documents mass flights of scientists and the impact on host-country innovation, generally highlighting benefits of migrant skills for hosts and calling for support to refugee scientists and to those staying in Ukraine. Reduced collaborations with Russia are expected to hurt Russian science. This paper quantifies how severely the war has hit the Ukrainian scientific community, focusing on brain drain, research time, and working conditions for scientists who stayed or migrated. It reports results from a representative online survey of 2,559 research-active employees of Ukrainian HEIs and PROs who worked in Ukraine when the war began, conducted between 21 September and 8 December 2022.

The literature on brain drain emphasizes the mobility of human capital and the potential long-term effects on home countries following extreme events like wars. Emigration of scientists, especially during conflict, may disproportionately involve the most productive individuals due to selection. Migrant scientists can benefit from learning, new resources, and higher productivity post-move, conditional on host environment opportunities; refugee contexts may involve suboptimal matches and incomplete integration. For home countries, losses include diminished local productivity, disrupted teams, and reduced training of future scientists, though mobile scientists can serve as bridges, enabling networks and knowledge flows; return migration can diffuse knowledge and practices back home. The ability of a country to benefit depends on whether emigrants maintain ties or eventually return. Less is known about how stayers fare during war, though exposure to extreme contexts brings stress and trauma that can impede research; destruction of infrastructure, power outages, and shifts of attention to safety, caregiving, or civil/military service further reduce research capacity. Ukrainian context: Historically, basic research was concentrated in National Academies of Sciences, with universities focused on teaching; incentives to conduct research at universities have increased post-Soviet transformation, but teaching remains primary, and Academies remain central to basic research. Estimates of research-active scientists range from about 41,000 FTE (2018) to 110,000 researchers (2020). By July 2023, 74 of ~300 universities were damaged or destroyed, with higher shares in Eastern and Southern regions. International support emerged for both movers and stayers (e.g., Science4Ukraine, ERA4Ukraine, mentoring programs, collaborative grants), though initiatives appeared more numerous or visible for migrants. Prior assessments: UAScience.reload surveys (spring/fall 2022) found 12–14.7% of scientists outside Ukraine; Maryl et al. (2022) reported many abroad maintained activities at home institutions with often reduced/no pay and mostly temporary foreign affiliations; bibliometric work suggests ~5% of prolific scientists publishing with foreign affiliation and ~10% decline in Ukrainian publication output relative to pre-war.

Survey design: Four waves conducted from 21 September to 8 December 2022. Eligibility required employment at a Ukrainian HEI or PRO at the start of the war and an average of at least 3 hours/week on research over the three pre-war years. Of 3,231 initial respondents, 413 were not employed in HEI/PRO at war start and 259 spent less than 3 hours/week on research pre-war; final eligible respondents numbered 2,559.

• Wave 1: Randomly targeted 6,996 scientists affiliated with Ukrainian institutions who had at least one publication in Web of Science or Scopus (2011–2021), using contact emails from publications. Received 1,188 answers (before filtering); adjusted response rate 19.3% (after 829 undeliverables). Non-response analysis feasible using inferred gender, region, and prolificacy.
• Waves 2–4: Disseminated via university corporate emails (from Ministry list), departmental contacts for top 100 universities, social media (Facebook Messenger, LinkedIn, Telegram, Viber, WhatsApp), NRFU communications, and a mailing list compiled from publications. Snowballing/referrals encouraged; response rates not applicable; limited information on non-respondents precluded non-response analysis for these waves. Representativeness and weighting: The combined sampling strategy ensured broad coverage but required adjustments. The sample overrepresented females (62.1% vs. 55% in population), underrepresented youngest (<30) and oldest (>64) age groups, and overrepresented 30–59; associate professors under-sampled; professors/senior researchers over-sampled; central regions (Kyiv, Kharkiv, Lviv) overrepresented; social sciences overrepresented; physical sciences underrepresented. Population benchmarks derived from Scopus authors (2019–2021) fractionally allocated across fields. Post-stratification weights computed following DeBell & Krosnick (2009) via the R package anesrake to match sample proportions to population across multiple characteristics; weights recomputed per analysis. No weights for sub-sample analyses (stayers vs. emigrants). Assumptions: all relevant observables included; no omitted unobservables correlated with outcomes. Given likely lower response among most-affected scientists, estimates of war effects are probably conservative. Measures and analyses: Outcomes included emigration (left Ukraine), departure from academia/research, changes in weekly research time (categorical: up to 3h; 3–5h; 5–10h; 10–20h; >20h), access to institutions and research inputs, and mobility within Ukraine. Research time hours were approximated by category midpoints (assuming 30 hours for >20h; 0 for up to 3h) for aggregate capacity estimates. Regression models: linear probability models for emigration and for leaving academia/research with covariates (pre-war research >20h/week, top 10% publications, PhD/ScD, lost access indicators, gender, age, region), with joint significance tests (F-test). Ordered logit models for changes in research time among stayers; multivariate regressions for institutional access constraints by region and demographics.

• Emigration: By fall 2022, an estimated 18.5% of Ukrainian scientists had left the country, similar to UNHCR’s estimate for the general population at that time. Emigration correlated with higher research activity/productivity: pre-war >20h/week researchers were 8 percentage points more likely to leave; top 10% by publications +12 pp; PhD/ScD +11 pp; these indicators jointly significant (F=7.417). Female scientists had a 5 pp higher probability of leaving; ~74% of movers were female.
• Exit from academia/research: 17.6% of surveyed scientists (migrants or not) were no longer in academia/research. Migrants were 17 pp more likely to have left academia/research than non-migrants. Scientists from South and East regions were more likely to exit academia/research, though not more likely to emigrate.
• Research capacity: Average weekly research time decreased from about 13 hours pre-war to about 10 hours during the war, implying roughly a 20% loss of research capacity. Qualitative evidence indicates reduced productivity due to psychological stress and disruptions, though some individuals reported increased writing.
• Emigrant scientists’ situation: Over 75% engaged with host scientists; ~30% had submitted a paper. Exposure to novelty was high (e.g., 64% reported large/very large exposure to new ideas), with 25–40% spending over 10% of time in entirely new fields. 87% believed the stay would improve their scientific abilities. About 58% were hosted by HEIs/PROs; among these, 89% held a contract (29% formal employment, 15% paid visiting, 45% scholarship). Only 26% of contracts exceeded one year; overall, ~14% of migrant scientists had secured a long-term academic contract. Approximately 2.5% of the total pre-war scientist population may not return to Ukraine. Engagement with Ukrainian colleagues declined, especially with those in Ukraine.
• Stayers’ situation: About 40% reported conducting less research than before; 10.1% stopped research entirely; 18.6% reduced to below 3 hours/week (threshold for non-research-active). 15.3% of stayers left academia. More productive scientists and National Academies researchers were better able to maintain research time, whereas those with >20h/week pre-war were more likely to report significant declines. 19.9% moved internally within Ukraine to safer regions. 23.5% lost access to essential research inputs. 20.7% could no longer access their institution in its original location (14.5% had online-only access; 4.2% had institution relocation). Scientists in East and South regions were more likely to face institutional access disruption.
• Long-term impact estimate: Assuming half of stayers who dropped out do not return to science and ~2.5% emigrants do not return to Ukraine, the country may have already lost about 7% of its scientists.

The study quantifies the war’s immediate effects on Ukrainian science, showing substantial emigration at rates similar to the general population but disproportionately concentrated among the most research-active and prolific scientists. This selection suggests a significant brain drain with potential knock-on effects on local collaboration, mentoring, and the training of PhD students. The observed 20% contraction in research capacity, combined with access disruptions and psychological stress, indicates that productivity losses may exceed what measured hours imply. Among migrants, high engagement and exposure to new ideas suggest potential gains in human and social capital that could benefit Ukraine upon return; however, precarious, short-term contracts and reduced ties with Ukrainian colleagues threaten future reintegration and knowledge flows. For stayers, widespread loss of access to institutions and inputs, internal displacement, and war-related infrastructure attacks severely impede research. Regional disparities (East/South) map to more intense disruptions. Overall, these findings address the research questions by documenting the magnitude and heterogeneity of brain drain, reduced research time, and working conditions for both migrants and stayers, and they underscore the importance of targeted policies to preserve scientific capacity and maintain diaspora-home ties during and after the conflict.

Based on a representative survey conducted from September to December 2022, the study finds that 18.5% of Ukrainian scientists emigrated by fall 2022, with departures concentrated among the most research-active and prolific. Research capacity shrank by roughly 20% in terms of hours devoted to research. Considering projected non-return among emigrants and sustained drop-outs among stayers, Ukraine may have already lost about 7% of its scientists. These immediate shocks portend longer-term consequences for training, mentorship, and competitiveness. Policy actions can mitigate losses: for migrants, prioritize more and longer scholarships and fellowships to ensure stability and deeper integration in host research environments; for stayers, provide remote visiting arrangements, access to digital libraries and computing resources, and collaborative research grants to sustain activity and keep international ties. The annual funding need for migrant support is estimated around €700 million (benchmarked to MSCA postdoctoral fellowships). Given constrained prospects for long-term positions in European institutions, policies should aim to maintain scientists within the global research community and facilitate eventual return and reintegration. Encouraging students’ return to Ukrainian universities post-war could also create opportunities for scientists. With sustained, concrete measures, the Ukrainian scientific sector can better withstand current disruptions and prepare for recovery and renewal.

The survey offers a snapshot conditioned on the context and timing of data collection; intentions (e.g., to return) may change as the war evolves. Despite efforts to ensure representativeness and use of post-stratification weights, potential non-response bias remains, particularly if the most affected scientists were less likely to respond (likely biasing estimates downward). Additional limitations include uneven regional representation, over/under-sampling of certain fields and ranks, reliance on self-reported categorical research time (masking within-category changes), and inability to weight or fully address attrition and selection in sub-samples of stayers and emigrants. Some dimensions—especially psychological impacts—are only indirectly captured due to survey design constraints. Follow-up waves are needed to assess long-term outcomes and dynamics.