Effective but Illegal: A Health Economics Analysis of the Black Market for GS-441524 in Treating Feline Infectious Peritonitis in China

Effective but Illegal: A Health Economics Analysis of the Black Market for GS-441524 in Treating Feline Infectious Peritonitis in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effective but Illegal: A Health Economics Analysis of the Black Market for GS-441524 in Treating Feline Infectious Peritonitis in China Shijun Wang, Shoujin Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9116812/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study evaluates the health economics of the small-molecule antiviral drug GS-441524 in treating Feline Infectious Peritonitis (FIP) within China's informal (black) market. It examines factors influencing pet owners' willingness to pay (WTP), tests the income elasticity of WTP, and estimates social welfare losses resulting from market distortions. Methods We conducted a cross-sectional online survey of Chinese pet owners (N = 201) who used black-market GS-441524 to treat cats with FIP during 2025. Data were collected on treatment costs, clinical outcomes, and WTP (using contingent valuation). Multiple linear regression models were constructed to analyze determinants of WTP and income elasticity. Consumer surplus, deadweight loss, and negative externalities were calculated. Probabilistic sensitivity analysis (PSA) was performed using 5,000 Monte Carlo simulations. Results Mean total treatment cost was 6,478 RMB (approximately 32 times estimated production cost), with a clinical cure rate of 68.2%. Median WTP was 13,543 RMB, yielding a mean consumer surplus of + 7,065 RMB. Critically, WTP exhibited strict "zero income elasticity": the coefficient of ln(income) was near zero and statistically insignificant (P > 0.9), indicating that psychological willingness to save a cat's life did not vary with owner income. Cat breed, age, and weight were also insignificant predictors of WTP. Interaction analysis confirmed this pattern across all city tiers, suggesting a "decommodification" of companion animal life in life-or-death decisions. PSA showed that at the median WTP threshold, the probability of black-market treatment being cost-effective was 98.3%. Nationally, estimated annual deadweight loss and negative externalities from this black market were approximately 59.8 million RMB and 48.9 million RMB, respectively. Conclusion While the black market for GS-441524 provides a clinical lifeline for cats with FIP, it imposes substantial social welfare losses through market failure. The finding of zero income elasticity reveals that in critical care decisions for companion animals, emotional bonds can transcend conventional budget constraints, leading to the "decommodification" of animal life. We recommend that authorities accelerate legal drug approval, implement cost-based pricing, and establish formal institutional mechanisms to replace informal compensation channels, thereby optimizing social welfare distribution. Feline Infectious Peritonitis GS-441524 Willingness to Pay Zero Income Elasticity Health Economics Black Market Figures Figure 1 Figure 2 Figure 3 1. Background 1. 1 Research Background: From "Incurable Disease" to Technological Breakthrough Feline Infectious Peritonitis (FIP) is a fatal, immune-mediated systemic disease caused by mutations in feline coronavirus (FCoV). Historically, FIP was considered an "incurable disease" in veterinary medicine due to its high mortality rate and complex pathogenesis [ 1 ] . Clinically, FIP manifests in effusive (wet), non-effusive (dry), or mixed forms, with symptoms including persistent fever, serous cavity effusion, neurological impairment, and ocular lesions [ 2 ] . The development of small-molecule antiviral drugs after 2018 revolutionized FIP treatment. Murphy et al. first demonstrated that the nucleoside analog GS-441524 potently inhibits FIP virus replication in vitro [ 3 ] . Subsequent clinical trials by Pedersen et al. reported survival rates exceeding 80% in treated cats [ 4 ] . This breakthrough fundamentally altered prognostic expectations and treatment decision-making for pet owners worldwide. 1.2 Formation of the Black Market in China: "Citizen Medicine" and Institutional Compensation Under Regulatory Vacuum Despite its demonstrated efficacy, GS-441524 has not obtained formal market authorization in China due to complex patent ownership and lengthy veterinary drug approval processes. This institutional supply gap, combined with strong treatment demand from pet owners, created a substantial supply-demand mismatch and catalyzed a large underground informal market. In this regulatory vacuum, a unique phenomenon of "citizen veterinary medicine" has emerged in China [ 5 ] . Unable to obtain the drug through legal channels, pet owners have turned to informal social networks (WeChat groups, Xiaohongshu, online forums) to seek treatment options. A decentralized, nationwide underground supply chain has developed, sourcing drugs through overseas proxy purchasing, domestic community group-buying, active pharmaceutical ingredients marketed as "research-grade chemicals," and preparations from private laboratories. This black market represents a form of "self-rescue" — a compensatory mechanism arising when formal institutions fail. However, the associated price volatility, quality uncertainty, and risks of unsupervised administration pose complex challenges for health economics and public governance. 1.3 Theoretical Significance: Zero Income Elasticity of WTP and the Decommodification of Companion Animal Life In classical health economics, willingness to pay (WTP) for mortality risk reduction or health gains typically exhibits positive income elasticity [ 10 ] . Under the rational actor model, health is considered a normal or even luxury good; as budget constraints loosen, higher-income groups are generally willing to pay more for life and health. This study examines and reveals a significant theoretical deviation in the context of critical medical decisions for companion animals: WTP exhibits strict zero income elasticity. Our empirical analysis shows that when facing life-or-death decisions for a companion animal, traditional economic rationality and budget constraints are largely superseded by deep emotional bonds. This homogeneous high WTP across income groups and geographical strata reflects a form of "cross-stratum altruism." In this decision context, the life of a companion animal acquires a "sacred value" that transcends conventional medical services, and its pricing logic becomes thoroughly "decommodified" [ 9 ] . 1.4 Research Objectives This study aims to: 1. Systematically quantify price distribution, cost composition, and financial burden of black-market GS-441524 for Chinese pet owners. 2. Analyze pet owners' WTP and its determinants, with particular focus on testing the income elasticity hypothesis. 3. Estimate consumer surplus, deadweight loss, and negative externalities associated with this black market. 4. Provide evidence-based policy recommendations for drug approval, pricing mechanism design, and market regulation. 2. Data and Methods 2. 1 Study Design and Sample Source This cross-sectional study assessed the economic impact of using black-market GS-441524 for FIP treatment based on micro-survey data. Chinese pet owners who used black-market drugs to treat cats with FIP during 2025 were purposively recruited via an online survey platform. The study protocol received ethics approval, and all respondents provided online informed consent. 2.2 Inclusion and Exclusion Criteria Respondents met all following criteria: ( 1) cat resided in Mainland China; (2) diagnosed with FIP by a veterinarian in the past 12 months (based on clinical signs, laboratory findings, or imaging); (3) drug obtained through informal (black market) channels; (4) treatment course lasted at least 4 weeks (or until endpoint events including death or euthanasia); (5) owner could provide detailed medical expenditure records and volunteered to participate. Technical measures excluded responses with missing key variables and duplicates (identified by IP address and cat characteristics). The final sample comprised 201 valid questionnaires, meeting medium-precision research requirements and comparing favorably with similar international studies. 2.3 Data Collection and Variable Definition The survey covered four dimensions: 1. Cat characteristics: breed, age, weight, clinical form (effusive/non-effusive). 2. Treatment and costs: drug source, formulation, administration route, comprehensive expenditures (diagnosis, medication, shipping). 3. Treatment outcomes: cure, death, euthanasia, or relapse. 4. Owner socioeconomic characteristics: monthly household income, education, administrative region. For the core research objective, we used the Contingent Valuation Method (CVM) to measure pet owners' maximum WTP to save their cat's life under a hypothetical scenario assuming > 80% cure rate. 2.4 Health Economics Evaluation Framework We constructed multi-dimensional economic evaluation indicators: Consumer surplus: difference between maximum WTP and actual cost. Deadweight loss: estimated using triangle approximation method, with benchmark equilibrium price based on production costs plus reasonable profit margin. Negative externalities: secondary expenditures from treatment failure and forgone tax revenue. To handle parameter uncertainty, we performed 5,000 Monte Carlo simulations (PSA). Cost variables and effectiveness (cure rate) were modeled with Gamma and Beta distributions, respectively. Cost-effectiveness acceptability curves (CEAC) and tornado diagrams were generated using Stata 17.0. 2.5 Statistical Analysis Statistical analysis was performed using Stata 17.0. Continuous variables were described using mean ± standard deviation or median (interquartile range) based on distribution. For empirical analysis, we constructed log-log multiple linear regression models with ln(WTP) as the dependent variable, focusing on the coefficient of ln(Income) to test the income elasticity hypothesis. Control variables included breed, age, weight, and owner's education. Province and city-tier fixed effects, as well as interaction terms between income and city tier, were introduced to examine heterogeneity. All statistical tests were two-sided with significance level set at P < 0.05. 3. Results 3. 1 Sample Characteristics 3.1.1 Basic Clinical Characteristics of Affected Cats The study included 201 cats with FIP treated with GS-441524 (Table 1 ). Mean age was 3.7 ± 2.2 years, and mean weight was 4.6 ± 1.3 kg. British/American Shorthairs (28.9%) and Chinese Domestic Cats (20.9%) were most common. Wet FIP accounted for 37.8% of cases, dry FIP for 32.3%, and uncertain/mixed forms for 29.9%. Only 28.9% of cases were confirmed by PCR testing, reflecting diagnostic challenges in the black-market context. Table 1 Basic Characteristics of Affected Cats (N = 201) Characteristic Dimension Statistics / Category Case (%) or Mean ± SD Biological Indicators Age (years) 3.7 ± 2.2 Weight (kg) 4.6 ± 1.3 Breed Distribution Dragon Li (Domestic Shorthair) 42 (20.9) British/American Shorthair 58 (28.9) Ragdoll 31 (15.4) Other Purebreds 38 (18.9) Mixed/Uncertain Breed 32 (15.9) Clinical Classification Effusive (Wet) FIP 76 (37.8) Non-effusive (Dry) FIP 65 (32.3) Uncertain/Mixed Form 60 (29.9) Diagnostic Method RT-PCR Testing 58 (28.9) Clinical Diagnosis by Veterinarian 75 (37.3) Uncertain/Presumptive 68 (33.8) 3.1.2 Socioeconomic Characteristics of Respondent Owners Respondents represented 26 Chinese provinces, concentrated in eastern coastal areas (Guangdong, Shandong, Jiangsu). The sample was highly educated, with 88. 1% holding a bachelor's degree or higher. Monthly household income distribution was relatively balanced (Table 2 ), with 16.9% of households reporting monthly income exceeding 30,000 RMB. Table 2 Owner Socioeconomic Characteristics (N = 201) Characteristic Indicator Category Case (%) Monthly Household Income 30,000 CNY 34 (16.9) Educational Attainment High School and Below 24 (11.9) Junior College / Bachelor's 94 (46.8) Master's and Above 83 (41.3) 3.2 Black Market Price Distribution and Treatment Cost Composition Mean total treatment cost was 6,478 RMB (median: 6,420 RMB; interquartile range: 4, 194–8,810 RMB). Cost composition (Table 4 ) showed diagnostic fees (32.7%) and drug costs (31.9%) as primary expenditure items, with shipping costs accounting for the smallest proportion (5.5%). Total costs did not differ significantly across drug sourcing channels (Table 3 ), suggesting the black market has developed relatively stable informal pricing mechanisms. Table 3 Total Treatment Costs by Drug Source Channel Sourcing Channel Case (%) Average Cost (CNY) Price Range (CNY) Overseas Purchasing Agent 54 (26.9) 6,520 4,703–8,810 Domestic Community Group Buying 64 (31.8) 6,400 4,588–8,579 Self-made Preparation 59 (29.4) 6,430 4,194–8,447 Other Channels 24 (11.9) 6,590 5,238–8,250 Table 4 Composition of Treatment Costs Cost Item Average Amount (CNY) Proportion (%) Medication Expenses 2,068 31.9 Diagnostic Expenses 2,115 32.7 Transportation Expenses 355 5.5 Other Related Expenses 1,940 30 Total 6,478 100 3.3 Treatment Outcomes and Economic Welfare Measures The sample cure rate was 68.2%, with death or euthanasia accounting for 17.9%. Mean maximum WTP (contingent valuation) was 13,543 RMB, significantly exceeding actual expenditure. This generated substantial consumer surplus (mean: +7,065 RMB; total sample surplus: 1.42 million RMB). However, 12.4% of respondents reported WTP lower than actual cost, indicating that some experienced extreme financial pressure or negative psychological surplus from black-market transactions. 3.4 Factors Influencing Willingness to Pay: Evidence for Zero Income Elasticity 3.4. 1 Core Finding: Zero Income Elasticity and Decommodification Table 5 presents baseline regression results after controlling for province fixed effects (Model M3). The coefficient for ln(Income) was 0.001 and statistically highly insignificant (P = 0.969). This finding strongly supports the zero-income-elasticity hypothesis: when facing life-or-death decisions for a companion animal, WTP does not vary with owner income. Whether monthly income was 3,000 RMB or 40,000 RMB, psychological willingness to save the cat's life remained unchanged. Furthermore, traditional "market attribute" variables—cat breed, age, weight—were not statistically significant. Compared to Chinese Domestic Cats, expensive breeds like Ragdolls or British Shorthairs did not command higher WTP premiums. This reinforces the decommodification thesis: in life-or-death situations, companion animals are valued as "family members" with non-commodity attributes, and life value achieves equality across breed characteristics in owners' valuation systems. Table 5 Determinants of ln(WTP): Province Fixed Effects Model (M3_Baseline) Variable Coefficient Robust Std. Err. P-value ln(Income) 0.001 0.033 0.969 Breed (Ref: Dragon Li / Domestic Shorthair) - British/American Shorthair -0.043 0.063 0.495 - Ragdoll 0.001 0.069 0.988 - Other Purebreds 0.027 0.071 0.704 - Mixed/Uncertain Breed -0.012 0.063 0.849 Age -0.007 0.012 0.56 Weight -0.019 0.019 0.317 Province Fixed Effects Controlled Constant 9.292 0.331 < 0.001 R-squared 0.208 Observations 201 Note: Full province fixed effects coefficients are shown in Table S1 . 3.4.2 Regional Heterogeneity: Geographic Variation in Emotional Valuation Although income and breed were insignificant, province fixed effects showed high significance, revealing geographic variation in WTP. Holding other variables constant, respondents in several provinces had significantly higher WTP than the baseline control group (P < 0.01): Tianjin (+ 0.639), Chongqing (+ 0.638), Shaanxi (+ 0.454), Fujian (+ 0.449), Shanxi (+ 0.391), Hebei (+ 0.385), and Shandong (+ 0.343). This suggests that valuation of companion animal emotions may be influenced by local pet community culture, mutual aid networks, and informal institutional environments. 3.4.3 Testing the Universality of Zero Income Elasticity: City-Tier Interaction Analysis To verify robustness across urban development levels, we introduced "monthly income × city tier" interaction terms (Table 6 ). All interaction terms were insignificant (P > 0.19), and the main effect of ln(Income) remained negligible across city tiers. This indicates that zero income elasticity exhibits significant cross-stratum universality—whether in resource-rich first-tier cities or fifth-tier cities with tighter budget constraints, pet owners' decision-making logic to save their cat's life showed high consistency. This pattern of "cross-stratum altruism" paints a collective picture of companion animals as "family members" among China's new generation of pet owners. Table 6 Heterogeneity Analysis: Income and City-Tier Interactions (M3_Interaction) Variable Coefficient Robust Std. Err. P-value ln(Income) 0.1 0.147 0.496 City Tier (Ref: Tier 1 Cities) - New Tier 1 2.594 2.572 0.314 - Tier 2 1.89 1.509 0.211 - Tier 3 0.763 1.807 0.673 - Tier 4 -0.028 1.449 0.985 - Tier 5 0.842 1.407 0.55 Interaction: Income×City Tier - New Tier 1 × ln(Income) -0.294 0.273 0.283 - Tier 2 × ln(Income) -0.214 0.165 0.195 - Tier 3 × ln(Income) -0.096 0.195 0.622 - Tier 4 × ln(Income) -0.018 0.161 0.909 - Tier 5 × ln(Income) -0.105 0.157 0.505 Breed, Age, Weight Controlled - - Province Fixed Effects Controlled - - Constant 8.752 1.32 < 0.001 R-squared 0.059 Observations 201 3.5Mechanism Analysis: From Willingness to Behavior and the First-Tier City "Price Paradox" To explore how psychological preferences translate into actual economic behavior, we regressed ln(Actual Cost) on owner and cat characteristics (Table 7 ). Several notable patterns emerged. First, there was a significant disconnect between WTP and actual cost. In both province fixed effects (M2_Province) and city-tier (M2_City) models, ln(WTP) had no significant effect on actual cost. Once treatment decisions were initiated, owners' subjective expectations did not predict final economic outlay. In the black-market context, pet owners were classic "price takers," with actual financial burden depending more on disease progression and local informal market conditions than on personal WTP. Second, breed variables showed an inverse association in the expenditure model. Compared to Chinese Domestic Cats, purebreds (British Shorthairs, American Shorthairs, Ragdolls) had significantly lower actual treatment costs (P < 0.05). This may reflect "preventive care" effects: purebred owners typically have higher health awareness and more mature pet-keeping experience, enabling earlier recognition of clinical signs and intervention. This "early detection, early intervention" pattern creates positive behavioral externalities, avoiding high-cost rescue treatments and complex complication management. Third, we observed a counter-intuitive first-tier city "price paradox." Despite having more transparent information networks and concentrated supply chains, first-tier cities exhibited significantly higher actual treatment costs. Costs in new first-tier through fifth-tier cities were 21.4% to 37. 1% lower than in first-tier cities (P < 0.01). This paradox suggests that resource agglomeration advantages in megacities are offset by higher diagnostic and treatment premiums, expensive ancillary testing, and more complex combination drug regimens. In critical care for companion animals, resource concentration may increase household financial burden through "overtreatment" or high support-service costs rather than producing economies of scale. Table 7 Determinants of ln(Actual Cost) Variable Model M2_State (State FE) Model M2_City (City Tier FE) ln(WTP) 0.070 (0.043) 0.023 (0.039) ln(Income) -0.012 (0.019) -0.003 (0.019) Breed (Ref: Dragon Li / Domestic Shorthair) - British/American Shorthair -0.092** (0.036) -0.027 (0.038) - Ragdoll -0.072* (0.041) -0.059 (0.041) - Other Purebreds -0.081** (0.037) -0.051 (0.039) - Mixed/Uncertain Breed -0.074** (0.036) -0.028 (0.040) Age -0.007 (0.012) -0.015 (0.012) Weight -0.020 (0.019) -0.010 (0.019) City Tier (Ref: Tier 1 Cities) - New Tier 1 - -0.371*** (0.077) - Tier 2 - -0.225*** (0.036) - Tier 3 - -0.272*** (0.046) - Tier 4 - -0.252*** (0.038) - Tier 5 - -0.214*** (0.032) - Other Tiers - -0.226*** (0.062) Province Fixed Effects Controlled Not Controlled R-squared 0.197 0.069 Observations 201 201 Note: Standard errors in parentheses; * P < 0.10, ** P < 0.05, *** P < 0.01 3.6 Probabilistic Sensitivity Analysis Probabilistic sensitivity analysis (PSA) with 5,000 Monte Carlo simulations accounted for parameter uncertainty. Figure 1 shows the cost-effectiveness acceptability curve (CEAC) for black-market treatment compared to "no treatment" (zero health outcome, zero cost). At a societal WTP threshold of 5,000 RMB, the probability of cost-effectiveness was 0%. However, at the median respondent WTP ( 13,543 RMB), cost-effectiveness probability rose to 98.3%. Using China's per capita GDP (approximately 85,000 RMB) as reference threshold, probability reached 100%. This indicates that under current black-market pricing, GS-441524 treatment remains highly economically valuable for most pet owners. One-way sensitivity analysis (tornado diagram, Fig. 2 ) revealed impact weights of parameter fluctuations on net monetary benefit (NMB). Cure rate fluctuations had slightly larger impact (range approximately ± 3,200 RMB) than treatment cost fluctuations (range approximately ± 3,000 RMB). At median WTP of 13,543 RMB, baseline NMB was 2,684 RMB, and NMB remained positive across all parameter variations. This indicates that while economic evaluation is somewhat sensitive to cure rate, overall conclusions remain robust under reasonable parameter uncertainty. Figure 3 presents the 5,000 Monte Carlo simulations on the cost-effectiveness plane. Scatter points clustered tightly around observed means (total cost 6,478 RMB, cure rate 68.2%), with baseline point (red 'X') in the central cluster. This tight clustering indicates that cost and effect estimates are highly robust despite random parameter variability. 3.7 Social Welfare Loss Estimation: Deadweight Loss and Negative Externalities To assess broader welfare impacts, we constructed a welfare economics model. Assuming our sample represents approximately 1% of total annual national cases (approximately 20, 100 cats treated nationally per year), we estimated: Deadweight loss (DWL): Using triangle approximation method, with black-market equilibrium price (P_BM) = 6,478 RMB, equilibrium quantity (Q_BM) = 20, 100. Assuming competitive market price (P_C) could drop to 500 RMB (based on production costs plus reasonable profit), and price elasticity would double demand (Q_C = 40,200), estimated annual DWL = 59.8 million RMB. Negative externalities: Total estimated at 48.89 million RMB, comprising: Treatment failure costs: 31.8% failure rate × assumed additional medical expenses of 5,000 RMB per failed case = 31.96 million RMB annually. Forgone tax revenue: National black-market transaction value estimated at 130.2 million RMB × 13% Value Added Tax = 16.93 million RMB annually. These estimates reveal that the black market for GS-441524 not only increases individual financial burden but also undermines overall social welfare through substantial deadweight loss and multi-dimensional negative externalities. While the informal market provides a "self-rescue" channel under regulatory vacuum, its underlying social costs are extremely high, necessitating formalization through market authorization and price intervention to optimize welfare distribution. 4. Discussion 4. 1 Theoretical Contribution: Zero Income Elasticity and the Decommodification Thesis This study reveals a unique economic behavior paradigm in companion animal medical decision-making. The finding of zero income elasticity challenges the classical health economics assumption that willingness to pay for health increases with income. When facing life-or-death decisions for their pets, individuals' economic budget constraints are largely superseded by deep emotional bonds. Companion animal life undergoes a process of "decommodification": market attributes such as breed, age, and weight become irrelevant, with Chinese Domestic Cats and expensive purebreds receiving equal emotional valuation in life-or-death situations. This homogeneous high WTP across regions and strata reflects "cross-stratum altruism" and aligns with psychological theories of "sacred values" [9]. When decision objects acquire inviolable moral significance, individuals resist rational cost-benefit trade-offs and follow behavioral rules of "absolute necessity." This study provides the first empirical validation of this phenomenon in health economics using micro-survey data and quantifies its welfare consequences. 4.2 Price Mechanisms and International Comparison Compared to international studies, GS-441524 in the Chinese black market exhibits a unique "price-efficacy" profile. Mean treatment cost (6,478 RMB, ~ 890 USD) is substantially lower than reported in US and UK studies (approximately 3, 100–4,920 USD). This price advantage may stem from low production costs due to China's mature chemical industry and channel premium compression through decentralized community group-buying models. However, the observed cure rate (68.2%) is slightly lower than foreign clinical trials and cohort studies. This may reflect unstable active ingredient concentrations in illegal drugs and the absence of professional veterinary guidance. The first-tier city "price paradox"—highest treatment costs in most resource-rich areas — further reveals erosion of household economic welfare by medical service premiums and "overtreatment" tendencies in large cities. According to the 2024 China Pet Medical Industry White Paper, average daily inpatient costs in first-tier cities are 1.8– 2.3 times those in second- and third-tier cities, consistent with our findings. 4.3 Welfare Loss and Policy Implications Welfare estimates show that the black market for GS-441524 causes substantial social resource misallocation. Annual deadweight loss of nearly 60 million RMB and negative externalities of nearly 50 million RMB reveal high social costs behind regulatory vacuum. Based on these findings, we propose the following policy recommendations. Table 8 Pathways for Formalizing FIP Treatment Market in China Core Issue Policy Intervention Recommendations Responsible Authorities Institutional Supply Shortage Establish a "green channel" for emergency veterinary drug access to accelerate the legalized registration and approval of GS-441524. During the transition period, grant licensed veterinarians limited clinical prescription rights by referencing human medicine management experience. Ministry of Agriculture and Rural Affairs (MARA), National Medical Products Administration (NMPA) Price Loss and Profiteering Implement a cost-oriented pricing mechanism; calculate and release industry-wide maximum retail price guidelines based on the production cost of active pharmaceutical ingredients (API) to squeeze out illegal black-market premiums. National Development and Reform Commission (NDRC), China Veterinary Medical Association (CVMA) Cost Premium in Major Cities Strengthen transparency in medical service fee supervision for animal hospitals in Tier 1 cities and crack down on over-treatment. Support commercial pet insurance to include FIP treatment in coverage catalogs to diversify family financial risks. State Administration for Market Regulation (SAMR), National Financial Regulatory Administration (NFRA), Local Industry Associations Low Supply Chain Transparency Acknowledge and standardize existing community group-buying models; integrate them into a formal regulatory system via digital platforms and establish drug traceability mechanisms to reduce information asymmetry. Ministry of Commerce (MOFCOM), Chinese Society of Animal Husbandry and Veterinary Medicine (CSAVM), Social Media Platforms 4.4 Limitations and Future Research This study has several limitations. First, recruitment through social platforms may introduce selection bias, potentially overrepresenting successful treatment cases. Second, cost and efficacy data relied on retrospective reports with potential recall bias. Third, lacking laboratory-level drug testing, we could not directly establish causal links between drug quality and clinical outcomes. Future research should focus on "real-world studies" following drug legalization, using large-sample longitudinal cohorts to monitor efficacy, resistance, and cost-effectiveness differences between black-market and formal drugs. Cross-cultural comparative studies exploring income elasticity of companion animal life valuation across different cultural backgrounds would deepen understanding of human-pet relationship economics. 5. Conclusion This health economics analysis of China's black market for GS-441524 reveals that while the informal market clinically saves many cats with FIP, underlying market failures are severe. Mean black-market treatment cost is 6,478 RMB—approximately 32 times production cost—and due to uncontrolled drug quality and lack of professional guidance, 31.8% of affected cats still face death or relapse. The most striking theoretical finding is strict zero income elasticity of willingness to pay: empirical results demonstrate that regardless of economic status, Chinese pet owners exhibit homogeneous high WTP to save their cats' lives. This transcendence of emotional bonds over economic rationality signifies profound "decommodification" of companion animal life in contemporary Chinese society, forming a collective consensus of "familial perception" across regions and strata. In actual transactions, owners' WTP does not effectively predict actual expenditure; pet owners are generally "price takers" passively bearing high costs. Significantly higher treatment costs in first-tier cities reveal severe erosion of household welfare by medical premiums in large cities. Estimates show that this black market generates annual deadweight loss of 59.8 million RMB and negative externalities of 48.89 million RMB—alarming social costs. Therefore, promoting legal market access for GS-441524 and establishing cost-oriented pricing systems are urgent policy priorities. Transforming black-market demand into formal medical demand is not only a rational choice for maximizing economic efficiency but also the most powerful humanistic response to countless instances of "cross-stratum love" in modern society. Declarations As independent researchers conducting a voluntary and anonymized online survey, formal institutional ethics committee approval was waived. However, the study was conducted in accordance with the ethical principles of the Declaration of Helsinki, and all respondents provided online informed consent prior to participating in the survey. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions WS formulated the research question, designed the study, conducted the statistical and health economic analysis, and drafted the original manuscript. LS contributed to the data collection, survey distribution, interpretation of results, and critically revised the manuscript for important intellectual content. Both authors read and approved the final manuscript. Acknowledgements Not applicable. References Pedersen NC. A review of feline infectious peritonitis virus infection: 1963–2008. J Feline Med Surg. 2009;11(4):225–58. Addie D, et al. Feline infectious peritonitis. ABCD guidelines on prevention and management. J Feline Med Surg. 2009;11(7):594–604. Murphy BG, et al. The nucleoside analog GS-441524 strongly inhibits feline infectious peritonitis (FIP) virus in tissue culture and experimental cats. Virology. 2018;525:167–75. Pedersen NC, et al. Efficacy and safety of the nucleoside analog GS-441524 for treatment of cats with naturally occurring feline infectious peritonitis. J Feline Med Surg. 2019;21(4):271–81. Evans SJM, et al. Citizen medicine in the feline infectious peritonitis epidemic: a new model of drug development? Front Vet Sci. 2021;8:654321. Jones S, et al. Unlicensed GS-441524-Like Antiviral Therapy Can Be Effective for at-Home Treatment ofFeline Infectious Peritonitis. Animals. 2021;11(8):2257. Negash R, et al. Owner experience and veterinary involvement with unlicensed GS-441524 treatment of feline infectious peritonitis: a prospective cohort study. Front Vet Sci. 2024;11:1377207. Kent AM, et al. Unlicensed antiviral products used for the at-home treatment of feline infectious peritonitis contain GS-441524 at significantly different amounts than advertised. J Am Vet Med Assoc. 2024;262(4):489–97. Tetlock PE. Thinking the unthinkable: sacred values and taboo cognitions. Trends Cogn Sci. 2003;7(7):320–4. Viscusi WK, Aldy JE. The Value of a Statistical Life: A Critical Review of Market Estimates Throughout the World. J Risk Uncertain. 2003;27(1):5–76. Additional Declarations No competing interests reported. Supplementary Files CHEER2022CheckList.xlsx SurveyQuestionnaireEnglishTranslationandChineseOriginal.docx SupplementaryInformations.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3QsQrCMBCA4UihLsE6Xgd1c04JBKEv01BolyKCSweHTNmkryL4Ai1CXeLeUSg4dfABRI04OdjWzSE/ZDjIx8EhZDL9Y7O6qG/kMXXeo9XHRCHBqUVd0Z8k8zFWFid5X0JyZSNX2gE9nkpAqc/FUJF2UmzLsyfxkqllBEjFXOCkgxxGMeES1ixPGAzkgQvURUrMoJCE77NGk7smTtNBFGauUAHfwWuL0AQ6triVHVKU5hSqhi6CMqYSLqtWMqqsotZ3mzpZ4lXXjT/JnHDXSj4L9LN/+G8ymUymLz0BqFVGUiwG7XAAAAAASUVORK5CYII=","orcid":"","institution":"Australian National University","correspondingAuthor":true,"prefix":"","firstName":"Shijun","middleName":"","lastName":"Wang","suffix":""},{"id":607746862,"identity":"b429cffb-cc25-4ac3-8f8f-842142adf522","order_by":1,"name":"Shoujin Li","email":"","orcid":"","institution":"Independent researcher","correspondingAuthor":false,"prefix":"","firstName":"Shoujin","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-03-13 16:40:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9116812/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9116812/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105038130,"identity":"5b4e1bd5-12b2-4117-a018-cd9b4887f8a9","added_by":"auto","created_at":"2026-03-20 07:42:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":155155,"visible":true,"origin":"","legend":"\u003cp\u003eCost-Effectiveness Acceptability Curve\u003c/p\u003e","description":"","filename":"IMG3478.png","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/51312d9afb088a5c69d41dd7.png"},{"id":105039139,"identity":"880f1fb8-1145-4b0b-8e77-707fbd9440fd","added_by":"auto","created_at":"2026-03-20 07:45:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114593,"visible":true,"origin":"","legend":"\u003cp\u003eTornado Diagram (One-Way Sensitivity Analysis)\u003c/p\u003e","description":"","filename":"17b162f9289ccc6c1f5f0966aeb48fea.png","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/f789d904d0e9dffd82b9c084.png"},{"id":105038162,"identity":"66a3b96f-b0fd-4a20-b7e6-cde8d6f10b66","added_by":"auto","created_at":"2026-03-20 07:42:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":764623,"visible":true,"origin":"","legend":"\u003cp\u003eCost-Effectiveness Scatter Plot\u003c/p\u003e","description":"","filename":"06cb9fbd3fb1f441e249822f6f0bc205.png","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/156523372be77d4c7d27c16a.png"},{"id":105567281,"identity":"809a7381-4dc6-498d-a8c0-2a433c0f36cd","added_by":"auto","created_at":"2026-03-27 12:58:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1689905,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/9054511f-5c2a-4449-b362-f10ff69810ed.pdf"},{"id":105038036,"identity":"82cf833e-9989-4ef2-8b77-47df4f9654a9","added_by":"auto","created_at":"2026-03-20 07:41:43","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16509,"visible":true,"origin":"","legend":"","description":"","filename":"CHEER2022CheckList.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/3d1cb9b3cb81df0e0e7c19b4.xlsx"},{"id":105038034,"identity":"3d3793cd-8678-487f-a933-6d2d64e92b25","added_by":"auto","created_at":"2026-03-20 07:41:43","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17754,"visible":true,"origin":"","legend":"","description":"","filename":"SurveyQuestionnaireEnglishTranslationandChineseOriginal.docx","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/6a0454611d8bb88022b06ef4.docx"},{"id":105038025,"identity":"104b84d0-7232-4612-9f5e-9b1d90ee8849","added_by":"auto","created_at":"2026-03-20 07:41:40","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1057778,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformations.docx","url":"https://assets-eu.researchsquare.com/files/rs-9116812/v1/b409c61a217885951808b604.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effective but Illegal: A Health Economics Analysis of the Black Market for GS-441524 in Treating Feline Infectious Peritonitis in China","fulltext":[{"header":"1. Background","content":"\u003cp\u003e1. 1 Research Background: From \"Incurable Disease\" to Technological Breakthrough\u003c/p\u003e \u003cp\u003eFeline Infectious Peritonitis (FIP) is a fatal, immune-mediated systemic disease caused by mutations in feline coronavirus (FCoV). Historically, FIP was considered an \"incurable disease\" in veterinary medicine due to its high mortality rate and complex pathogenesis\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Clinically, FIP manifests in effusive (wet), non-effusive (dry), or mixed forms, with symptoms including persistent fever, serous cavity effusion, neurological impairment, and ocular lesions\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe development of small-molecule antiviral drugs after 2018 revolutionized FIP treatment. Murphy et al. first demonstrated that the nucleoside analog GS-441524 potently inhibits FIP virus replication in vitro\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Subsequent clinical trials by Pedersen et al. reported survival rates exceeding 80% in treated cats \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. This breakthrough fundamentally altered prognostic expectations and treatment decision-making for pet owners worldwide.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Formation of the Black Market in China: \"Citizen Medicine\" and Institutional Compensation Under Regulatory Vacuum\u003c/h2\u003e \u003cp\u003e Despite its demonstrated efficacy, GS-441524 has not obtained formal market authorization in China due to complex patent ownership and lengthy veterinary drug approval processes. This institutional supply gap, combined with strong treatment demand from pet owners, created a substantial supply-demand mismatch and catalyzed a large underground informal market.\u003c/p\u003e \u003cp\u003eIn this regulatory vacuum, a unique phenomenon of \"citizen veterinary medicine\" has emerged in China\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Unable to obtain the drug through legal channels, pet owners have turned to informal social networks (WeChat groups, Xiaohongshu, online forums) to seek treatment options. A decentralized, nationwide underground supply chain has developed, sourcing drugs through overseas proxy purchasing, domestic community group-buying, active pharmaceutical ingredients marketed as \"research-grade chemicals,\" and preparations from private laboratories. This black market represents a form of \"self-rescue\" \u0026mdash; a compensatory mechanism arising when formal institutions fail. However, the associated price volatility, quality uncertainty, and risks of unsupervised administration pose complex challenges for health economics and public governance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Theoretical Significance: Zero Income Elasticity of WTP and the Decommodification of Companion Animal Life\u003c/h2\u003e \u003cp\u003eIn classical health economics, willingness to pay (WTP) for mortality risk reduction or health gains typically exhibits positive income elasticity\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Under the rational actor model, health is considered a normal or even luxury good; as budget constraints loosen, higher-income groups are generally willing to pay more for life and health.\u003c/p\u003e \u003cp\u003eThis study examines and reveals a significant theoretical deviation in the context of critical medical decisions for companion animals: WTP exhibits strict zero income elasticity. Our empirical analysis shows that when facing life-or-death decisions for a companion animal, traditional economic rationality and budget constraints are largely superseded by deep emotional bonds. This homogeneous high WTP across income groups and geographical strata reflects a form of \"cross-stratum altruism.\" In this decision context, the life of a companion animal acquires a \"sacred value\" that transcends conventional medical services, and its pricing logic becomes thoroughly \"decommodified\"\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e1.4 Research Objectives This study aims to:\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e1. Systematically quantify price distribution, cost composition, and financial burden of black-market GS-441524 for Chinese pet owners.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e2. Analyze pet owners' WTP and its determinants, with particular focus on testing the income elasticity hypothesis.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e3. Estimate consumer surplus, deadweight loss, and negative externalities associated with this black market.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e4. Provide evidence-based policy recommendations for drug approval, pricing mechanism design, and market regulation.\u003c/p\u003e \u003c/li\u003e\u003c/ol\u003e"},{"header":"2. Data and Methods","content":"\u003cp\u003e2. 1 Study Design and Sample Source\u003c/p\u003e\u003cp\u003eThis cross-sectional study assessed the economic impact of using black-market GS-441524 for FIP treatment based on micro-survey data. Chinese pet owners who used black-market drugs to treat cats with FIP during 2025 were purposively recruited via an online survey platform. The study protocol received ethics approval, and all respondents provided online informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003eRespondents met all following criteria: ( 1) cat resided in Mainland China; (2) diagnosed with FIP by a veterinarian in the past 12 months (based on clinical signs, laboratory findings, or imaging); (3) drug obtained through informal (black market) channels; (4) treatment course lasted at least 4 weeks (or until endpoint events including death or euthanasia); (5) owner could provide detailed medical expenditure records and volunteered to participate. Technical measures excluded responses with missing key variables and duplicates (identified by IP address and cat characteristics). The final sample comprised 201 valid questionnaires, meeting medium-precision research requirements and comparing favorably with similar international studies.\u003c/p\u003e\u003cp\u003e2.3 Data Collection and Variable Definition The survey covered four dimensions:\u003c/p\u003e\u003cp\u003e1. Cat characteristics: breed, age, weight, clinical form (effusive/non-effusive).\u003c/p\u003e\u003cp\u003e2. Treatment and costs: drug source, formulation, administration route, comprehensive expenditures (diagnosis, medication, shipping).\u003c/p\u003e\u003cp\u003e3. Treatment outcomes: cure, death, euthanasia, or relapse.\u003c/p\u003e\u003cp\u003e4. Owner socioeconomic characteristics: monthly household income, education, administrative region.\u003c/p\u003e\u003cp\u003eFor the core research objective, we used the Contingent Valuation Method (CVM) to measure pet owners' maximum WTP to save their cat's life under a hypothetical scenario assuming\u0026thinsp;\u0026gt;\u0026thinsp;80% cure rate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Health Economics Evaluation Framework\u003c/h2\u003e \u003cp\u003eWe constructed multi-dimensional economic evaluation indicators:\u003c/p\u003e \u003cp\u003eConsumer surplus: difference between maximum WTP and actual cost.\u003c/p\u003e \u003cp\u003eDeadweight loss: estimated using triangle approximation method, with benchmark equilibrium price based on production costs plus reasonable profit margin.\u003c/p\u003e \u003cp\u003eNegative externalities: secondary expenditures from treatment failure and forgone tax revenue.\u003c/p\u003e \u003cp\u003eTo handle parameter uncertainty, we performed 5,000 Monte Carlo simulations (PSA). Cost variables and effectiveness (cure rate) were modeled with Gamma and Beta distributions, respectively. Cost-effectiveness acceptability curves (CEAC) and tornado diagrams were generated using Stata 17.0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using Stata 17.0. Continuous variables were described using mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range) based on distribution. For empirical analysis, we constructed log-log multiple linear regression models with ln(WTP) as the dependent variable, focusing on the coefficient of ln(Income) to test the income elasticity hypothesis. Control variables included breed, age, weight, and owner's education. Province and city-tier fixed effects, as well as interaction terms between income and city tier, were introduced to examine heterogeneity. All statistical tests were two-sided with significance level set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e3. 1 Sample Characteristics\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003cdiv class=\"Heading\"\u003e3.1.1 Basic Clinical Characteristics of Affected Cats\u003c/div\u003e \u003cp\u003eThe study included 201 cats with FIP treated with GS-441524 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mean age was 3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 years, and mean weight was 4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 kg. British/American Shorthairs (28.9%) and Chinese Domestic Cats (20.9%) were most common. Wet FIP accounted for 37.8% of cases, dry FIP for 32.3%, and uncertain/mixed forms for 29.9%. Only 28.9% of cases were confirmed by PCR testing, reflecting diagnostic challenges in the black-market context.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic Characteristics of Affected Cats (N\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic Dimension\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistics / Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase (%) or Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBiological Indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eBreed Distribution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDragon Li (Domestic Shorthair)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (20.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBritish/American Shorthair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (28.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRagdoll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Purebreds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (18.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMixed/Uncertain Breed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eClinical Classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEffusive (Wet) FIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (37.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-effusive (Dry) FIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUncertain/Mixed Form\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (29.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDiagnostic Method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRT-PCR Testing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (28.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical Diagnosis by Veterinarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (37.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUncertain/Presumptive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (33.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003cdiv class=\"Heading\"\u003e3.1.2 Socioeconomic Characteristics of Respondent Owners\u003c/div\u003e \u003cp\u003eRespondents represented 26 Chinese provinces, concentrated in eastern coastal areas (Guangdong, Shandong, Jiangsu). The sample was highly educated, with 88. 1% holding a bachelor's degree or higher. Monthly household income distribution was relatively balanced (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with 16.9% of households reporting monthly income exceeding 30,000 RMB.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOwner Socioeconomic Characteristics (N\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic Indicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eMonthly Household Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5,000 CNY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36 (17.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,000\u0026ndash;10,000 CNY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47 (23.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,001\u0026ndash;20,000 CNY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49 (24.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,001\u0026ndash;30,000 CNY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35 (17.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30,000 CNY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (16.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducational Attainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School and Below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (11.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior College / Bachelor's\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94 (46.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaster's and Above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83 (41.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Black Market Price Distribution and Treatment Cost Composition\u003c/h2\u003e \u003cp\u003eMean total treatment cost was 6,478 RMB (median: 6,420 RMB; interquartile range: 4, 194\u0026ndash;8,810 RMB). Cost composition (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) showed diagnostic fees (32.7%) and drug costs (31.9%) as primary expenditure items, with shipping costs accounting for the smallest proportion (5.5%). Total costs did not differ significantly across drug sourcing channels (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), suggesting the black market has developed relatively stable informal pricing mechanisms.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal Treatment Costs by Drug Source Channel\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSourcing Channel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCase (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage Cost (CNY)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrice Range (CNY)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverseas Purchasing Agent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,703\u0026ndash;8,810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomestic Community Group Buying\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,588\u0026ndash;8,579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-made Preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,194\u0026ndash;8,447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Channels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,238\u0026ndash;8,250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComposition of Treatment Costs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost Item\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage Amount (CNY)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication Expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic Expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation Expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Related Expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Treatment Outcomes and Economic Welfare Measures\u003c/h2\u003e \u003cp\u003eThe sample cure rate was 68.2%, with death or euthanasia accounting for 17.9%. Mean maximum WTP (contingent valuation) was 13,543 RMB, significantly exceeding actual expenditure. This generated substantial consumer surplus (mean: +7,065 RMB; total sample surplus: 1.42\u0026nbsp;million RMB). However, 12.4% of respondents reported WTP lower than actual cost, indicating that some experienced extreme financial pressure or negative psychological surplus from black-market transactions.\u003c/p\u003e \u003cp\u003e3.4 Factors Influencing Willingness to Pay: Evidence for Zero Income Elasticity\u003c/p\u003e\u003cp\u003e3.4. 1 Core Finding: Zero Income Elasticity and Decommodification\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents baseline regression results after controlling for province fixed effects (Model M3). The coefficient for ln(Income) was 0.001 and statistically highly insignificant (P\u0026thinsp;=\u0026thinsp;0.969). This finding strongly supports the zero-income-elasticity hypothesis: when facing life-or-death decisions for a companion animal, WTP does not vary with owner income. Whether monthly\u003c/p\u003e \u003cp\u003eincome was 3,000 RMB or 40,000 RMB, psychological willingness to save the cat's life remained unchanged.\u003c/p\u003e \u003cp\u003eFurthermore, traditional \"market attribute\" variables\u0026mdash;cat breed, age, weight\u0026mdash;were not statistically significant. Compared to Chinese Domestic Cats, expensive breeds like Ragdolls or British Shorthairs did not command higher WTP premiums. This reinforces the decommodification thesis: in life-or-death situations, companion animals are valued as \"family members\" with non-commodity attributes, and life value achieves equality across breed characteristics in owners' valuation systems.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDeterminants of ln(WTP): Province Fixed Effects Model (M3_Baseline)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRobust Std. Err.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eBreed (Ref: Dragon Li / Domestic Shorthair)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- British/American Shorthair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Ragdoll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Other Purebreds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Mixed/Uncertain Breed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvince Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControlled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: Full province fixed effects coefficients are shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 Regional Heterogeneity: Geographic Variation in Emotional Valuation\u003c/h2\u003e \u003cp\u003eAlthough income and breed were insignificant, province fixed effects showed high significance, revealing geographic variation in WTP. Holding other variables constant, respondents in several provinces had significantly higher WTP than the baseline control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01): Tianjin (+\u0026thinsp;0.639), Chongqing (+\u0026thinsp;0.638), Shaanxi (+\u0026thinsp;0.454), Fujian (+\u0026thinsp;0.449), Shanxi (+\u0026thinsp;0.391), Hebei (+\u0026thinsp;0.385), and Shandong (+\u0026thinsp;0.343). This suggests that valuation of companion animal emotions may be influenced by local pet community culture, mutual aid networks, and informal institutional environments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.4.3 Testing the Universality of Zero Income Elasticity: City-Tier Interaction Analysis\u003c/h2\u003e \u003cp\u003eTo verify robustness across urban development levels, we introduced \"monthly income \u0026times; city tier\" interaction terms (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). All interaction terms were insignificant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.19), and the main effect of ln(Income) remained negligible across city tiers. This indicates that zero income elasticity exhibits significant cross-stratum universality\u0026mdash;whether in resource-rich first-tier cities or fifth-tier cities with tighter budget constraints, pet owners' decision-making logic to save their cat's life showed high consistency. This pattern of \"cross-stratum altruism\" paints a collective picture of companion animals as \"family members\" among China's new generation of pet owners.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeterogeneity Analysis: Income and City-Tier Interactions (M3_Interaction)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRobust Std. Err.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCity Tier (Ref: Tier 1 Cities)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- New Tier 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eInteraction: Income\u0026times;City Tier\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- New Tier 1 \u0026times; ln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 2 \u0026times; ln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 3 \u0026times; ln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 4 \u0026times; ln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 5 \u0026times; ln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreed, Age, Weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControlled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvince Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControlled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5Mechanism Analysis: From Willingness to Behavior and the First-Tier City \"Price Paradox\"\u003c/h2\u003e \u003cp\u003eTo explore how psychological preferences translate into actual economic behavior, we regressed ln(Actual Cost) on owner and cat characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Several notable patterns emerged.\u003c/p\u003e \u003cp\u003eFirst, there was a significant disconnect between WTP and actual cost. In both province fixed effects (M2_Province) and city-tier (M2_City) models, ln(WTP) had no significant effect on actual cost. Once treatment decisions were initiated, owners' subjective expectations did not predict final economic outlay. In the black-market context, pet owners were classic \"price takers,\" with actual financial burden depending more on disease progression and local informal market conditions than on personal WTP.\u003c/p\u003e \u003cp\u003eSecond, breed variables showed an inverse association in the expenditure model. Compared to Chinese Domestic Cats, purebreds (British Shorthairs, American Shorthairs, Ragdolls) had significantly lower actual treatment costs (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This may reflect \"preventive care\" effects: purebred owners typically have higher health awareness and more mature pet-keeping experience, enabling earlier recognition of clinical signs and intervention. This \"early detection, early intervention\" pattern creates positive behavioral externalities, avoiding high-cost rescue treatments and complex complication management.\u003c/p\u003e \u003cp\u003eThird, we observed a counter-intuitive first-tier city \"price paradox.\" Despite having more transparent information networks and concentrated supply chains, first-tier cities exhibited significantly higher actual treatment costs. Costs in new first-tier through fifth-tier cities were 21.4% to 37. 1% lower than in first-tier cities (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This paradox suggests that resource agglomeration advantages in megacities are offset by higher diagnostic and treatment premiums, expensive ancillary testing, and more complex combination drug regimens. In critical care for companion animals, resource concentration may increase household financial burden through \"overtreatment\" or high support-service costs rather than producing economies of scale.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDeterminants of ln(Actual Cost)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel M2_State (State FE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel M2_City (City Tier FE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eln(WTP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003cp\u003e(0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eln(Income)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eBreed (Ref: Dragon Li / Domestic Shorthair)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- British/American Shorthair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.092**\u003c/p\u003e \u003cp\u003e(0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.027\u003c/p\u003e \u003cp\u003e(0.038)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Ragdoll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.072*\u003c/p\u003e \u003cp\u003e(0.041)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.059\u003c/p\u003e \u003cp\u003e(0.041)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Other Purebreds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.081**\u003c/p\u003e \u003cp\u003e(0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003cp\u003e(0.039)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Mixed/Uncertain Breed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.074**\u003c/p\u003e \u003cp\u003e(0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003cp\u003e(0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003cp\u003e(0.012)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCity Tier (Ref: Tier 1 Cities)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- New Tier 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.371*** (0.077)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.225*** (0.036)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.272*** (0.046)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.252*** (0.038)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Tier 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.214*** (0.032)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Other Tiers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.226*** (0.062)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvince Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControlled\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Controlled\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNote: Standard errors in parentheses; * P\u0026thinsp;\u0026lt;\u0026thinsp;0.10, ** P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *** P\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Probabilistic Sensitivity Analysis\u003c/h2\u003e \u003cp\u003eProbabilistic sensitivity analysis (PSA) with 5,000 Monte Carlo simulations accounted for parameter uncertainty. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the cost-effectiveness acceptability curve (CEAC) for black-market treatment compared to \"no treatment\" (zero health outcome, zero cost). At a societal WTP threshold of 5,000 RMB, the probability of cost-effectiveness was 0%. However, at the median respondent WTP ( 13,543 RMB), cost-effectiveness probability rose to 98.3%. Using China's per capita GDP (approximately 85,000 RMB) as reference threshold, probability reached 100%. This indicates that under current black-market pricing, GS-441524 treatment remains highly economically valuable for most pet owners.\u003c/p\u003e \u003cp\u003eOne-way sensitivity analysis (tornado diagram, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed impact weights of parameter fluctuations on net monetary benefit (NMB). Cure rate fluctuations had slightly larger impact (range approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;3,200 RMB) than treatment cost fluctuations (range approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;3,000 RMB). At median WTP of 13,543 RMB, baseline NMB was 2,684 RMB, and NMB remained positive across all parameter variations. This indicates that while economic evaluation is somewhat sensitive to cure rate, overall conclusions remain robust under reasonable parameter uncertainty.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the 5,000 Monte Carlo simulations on the cost-effectiveness plane. Scatter points clustered tightly around observed means (total cost 6,478 RMB, cure rate 68.2%), with baseline point (red 'X') in the central cluster. This tight clustering indicates that cost and effect estimates are highly robust despite random parameter variability.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Social Welfare Loss Estimation: Deadweight Loss and Negative Externalities\u003c/h2\u003e \u003cp\u003eTo assess broader welfare impacts, we constructed a welfare economics model. Assuming our sample represents approximately 1% of total annual national cases (approximately 20, 100 cats treated nationally per year), we estimated:\u003c/p\u003e \u003cp\u003eDeadweight loss (DWL): Using triangle approximation method, with black-market equilibrium price (P_BM)\u0026thinsp;=\u0026thinsp;6,478 RMB, equilibrium quantity (Q_BM)\u0026thinsp;=\u0026thinsp;20, 100. Assuming competitive market price (P_C) could drop to 500 RMB (based on production costs plus reasonable profit), and price elasticity would double demand (Q_C\u0026thinsp;=\u0026thinsp;40,200), estimated annual DWL\u0026thinsp;=\u0026thinsp;59.8\u0026nbsp;million RMB.\u003c/p\u003e \u003cp\u003eNegative externalities: Total estimated at 48.89\u0026nbsp;million RMB, comprising:\u003c/p\u003e \u003cp\u003eTreatment failure costs: 31.8% failure rate \u0026times; assumed additional medical expenses of 5,000 RMB per failed case\u0026thinsp;=\u0026thinsp;31.96\u0026nbsp;million RMB annually.\u003c/p\u003e \u003cp\u003eForgone tax revenue: National black-market transaction value estimated at 130.2\u0026nbsp;million RMB \u0026times; 13% Value Added Tax\u0026thinsp;=\u0026thinsp;16.93\u0026nbsp;million RMB annually.\u003c/p\u003e \u003cp\u003eThese estimates reveal that the black market for GS-441524 not only increases individual financial burden but also undermines overall social welfare through substantial deadweight loss and multi-dimensional negative externalities. While the informal market provides a \"self-rescue\" channel under regulatory vacuum, its underlying social costs are extremely high, necessitating formalization through market authorization and price intervention to optimize welfare distribution.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e4. 1 Theoretical Contribution: Zero Income Elasticity and the Decommodification Thesis\u003c/p\u003e \u003cp\u003eThis study reveals a unique economic behavior paradigm in companion animal medical decision-making. The finding of zero income elasticity challenges the classical health economics assumption that willingness to pay for health increases with income. When facing life-or-death decisions for their pets, individuals' economic budget constraints are largely superseded by deep emotional bonds. Companion animal life undergoes a process of \"decommodification\": market attributes such as breed, age, and weight become irrelevant, with Chinese Domestic Cats and expensive purebreds receiving equal emotional valuation in life-or-death situations.\u003c/p\u003e \u003cp\u003eThis homogeneous high WTP across regions and strata reflects \"cross-stratum altruism\" and aligns with psychological theories of \"sacred values\" [9]. When decision objects acquire inviolable moral significance, individuals resist rational cost-benefit trade-offs and follow behavioral rules of \"absolute necessity.\" This study provides the first empirical validation of this phenomenon in health economics using micro-survey data and quantifies its welfare consequences.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Price Mechanisms and International Comparison\u003c/h2\u003e \u003cp\u003eCompared to international studies, GS-441524 in the Chinese black market exhibits a unique \"price-efficacy\" profile. Mean treatment cost (6,478 RMB, ~\u0026thinsp;890 USD) is substantially lower than reported in US and UK studies (approximately 3, 100\u0026ndash;4,920 USD). This price advantage may stem from low production costs due to China's mature chemical industry and channel premium compression through decentralized community group-buying models.\u003c/p\u003e \u003cp\u003eHowever, the observed cure rate (68.2%) is slightly lower than foreign clinical trials and cohort studies. This may reflect unstable active ingredient concentrations in illegal drugs and the absence of professional veterinary guidance. The first-tier city \"price paradox\"\u0026mdash;highest treatment costs in most resource-rich areas \u0026mdash; further reveals erosion of household economic welfare by medical service premiums and \"overtreatment\" tendencies in large cities. According to the 2024 China Pet Medical Industry White Paper, average daily inpatient costs in first-tier cities are 1.8\u0026ndash; 2.3 times those in second- and third-tier cities, consistent with our findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Welfare Loss and Policy Implications\u003c/h2\u003e \u003cp\u003eWelfare estimates show that the black market for GS-441524 causes substantial social resource misallocation. Annual deadweight loss of nearly 60\u0026nbsp;million RMB and negative externalities of nearly 50\u0026nbsp;million RMB reveal high social costs behind regulatory vacuum. Based on these findings, we propose the following policy recommendations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePathways for Formalizing FIP Treatment Market in China\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCore Issue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolicy Intervention Recommendations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResponsible Authorities\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional Supply Shortage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstablish a \"green channel\" for emergency veterinary drug access to accelerate the legalized registration and approval of GS-441524. During the transition period, grant licensed veterinarians limited clinical prescription rights by referencing human medicine management experience.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinistry of Agriculture and Rural Affairs (MARA), National Medical Products Administration (NMPA)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrice Loss and Profiteering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImplement a cost-oriented pricing mechanism; calculate and release industry-wide maximum retail price guidelines based on the production cost of active pharmaceutical ingredients (API) to squeeze out illegal black-market premiums.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNational Development and Reform Commission (NDRC), China Veterinary Medical Association (CVMA)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost Premium in Major Cities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrengthen transparency in medical service fee supervision for animal hospitals in Tier 1 cities and crack down on over-treatment. Support commercial pet insurance to include FIP treatment in coverage catalogs to diversify family financial risks.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eState Administration for Market Regulation (SAMR), National Financial Regulatory Administration (NFRA), Local Industry Associations\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Supply Chain Transparency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcknowledge and standardize existing community group-buying models; integrate them into a formal regulatory system via digital platforms and establish drug traceability mechanisms to reduce information asymmetry.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinistry of Commerce (MOFCOM), Chinese Society of Animal Husbandry and Veterinary Medicine (CSAVM), Social Media Platforms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Limitations and Future Research\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, recruitment through social platforms may introduce selection bias, potentially overrepresenting successful treatment cases. Second, cost and efficacy data relied on retrospective reports with potential recall bias. Third, lacking laboratory-level drug testing, we could not directly establish causal links between drug quality and clinical outcomes.\u003c/p\u003e \u003cp\u003eFuture research should focus on \"real-world studies\" following drug legalization, using large-sample longitudinal cohorts to monitor efficacy, resistance, and cost-effectiveness differences between black-market and formal drugs. Cross-cultural comparative studies exploring income elasticity of companion animal life valuation across different cultural backgrounds would deepen understanding of human-pet relationship economics.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis health economics analysis of China's black market for GS-441524 reveals that while the informal market clinically saves many cats with FIP, underlying market failures are severe. Mean black-market treatment cost is 6,478 RMB\u0026mdash;approximately 32 times production cost\u0026mdash;and due to uncontrolled drug quality and lack of professional guidance, 31.8% of affected cats still face death or relapse.\u003c/p\u003e \u003cp\u003eThe most striking theoretical finding is strict zero income elasticity of willingness to pay: empirical results demonstrate that regardless of economic status, Chinese pet owners exhibit homogeneous high WTP to save their cats' lives. This transcendence of emotional bonds over economic rationality signifies profound \"decommodification\" of companion animal life in contemporary Chinese society, forming a collective consensus of \"familial perception\" across regions and strata.\u003c/p\u003e \u003cp\u003eIn actual transactions, owners' WTP does not effectively predict actual expenditure; pet owners are generally \"price takers\" passively bearing high costs. Significantly higher treatment costs in first-tier cities reveal severe erosion of household welfare by medical premiums in large cities.\u003c/p\u003e \u003cp\u003eEstimates show that this black market generates annual deadweight loss of 59.8\u0026nbsp;million RMB and negative externalities of 48.89\u0026nbsp;million RMB\u0026mdash;alarming social costs. Therefore, promoting legal market access for GS-441524 and establishing cost-oriented pricing systems are urgent policy priorities. Transforming black-market demand into formal medical demand is not only a rational choice for maximizing economic efficiency but also the most powerful humanistic response to countless instances of \"cross-stratum love\" in modern society.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAs independent researchers conducting a voluntary and anonymized online survey, formal institutional ethics committee approval was waived. However, the study was conducted in accordance with the ethical principles of the Declaration of Helsinki, and all respondents provided online informed consent prior to participating in the survey.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003eAuthors' contributions\u003c/p\u003e\n\u003cp\u003eWS formulated the research question, designed the study, conducted the statistical and health economic analysis, and drafted the original manuscript. LS contributed to the data collection, survey distribution, interpretation of results, and critically revised the manuscript for important intellectual content. Both authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePedersen NC. A review of feline infectious peritonitis virus infection: 1963\u0026ndash;2008. J Feline Med Surg. 2009;11(4):225\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAddie D, et al. Feline infectious peritonitis. ABCD guidelines on prevention and management. J Feline Med Surg. 2009;11(7):594\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurphy BG, et al. The nucleoside analog GS-441524 strongly inhibits feline infectious peritonitis (FIP) virus in tissue culture and experimental cats. Virology. 2018;525:167\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedersen NC, et al. Efficacy and safety of the nucleoside analog GS-441524 for treatment of cats with naturally occurring feline infectious peritonitis. J Feline Med Surg. 2019;21(4):271\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans SJM, et al. Citizen medicine in the feline infectious peritonitis epidemic: a new model of drug development? Front Vet Sci. 2021;8:654321.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones S, et al. Unlicensed GS-441524-Like Antiviral Therapy Can Be Effective for at-Home Treatment ofFeline Infectious Peritonitis. Animals. 2021;11(8):2257.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNegash R, et al. Owner experience and veterinary involvement with unlicensed GS-441524 treatment of feline infectious peritonitis: a prospective cohort study. Front Vet Sci. 2024;11:1377207.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKent AM, et al. Unlicensed antiviral products used for the at-home treatment of feline infectious peritonitis contain GS-441524 at significantly different amounts than advertised. J Am Vet Med Assoc. 2024;262(4):489\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTetlock PE. Thinking the unthinkable: sacred values and taboo cognitions. Trends Cogn Sci. 2003;7(7):320\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eViscusi WK, Aldy JE. The Value of a Statistical Life: A Critical Review of Market Estimates Throughout the World. J Risk Uncertain. 2003;27(1):5\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Feline Infectious Peritonitis, GS-441524, Willingness to Pay, Zero Income Elasticity, Health Economics, Black Market","lastPublishedDoi":"10.21203/rs.3.rs-9116812/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9116812/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study evaluates the health economics of the small-molecule antiviral drug GS-441524 in treating Feline Infectious Peritonitis (FIP) within China's informal (black) market. It examines factors influencing pet owners' willingness to pay (WTP), tests the income elasticity of WTP, and estimates social welfare losses resulting from market distortions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional online survey of Chinese pet owners (N\u0026thinsp;=\u0026thinsp;201) who used black-market GS-441524 to treat cats with FIP during 2025. Data were collected on treatment costs, clinical outcomes, and WTP (using contingent valuation). Multiple linear regression models were constructed to analyze determinants of WTP and income elasticity. Consumer surplus, deadweight loss, and negative externalities were calculated. Probabilistic sensitivity analysis (PSA) was performed using 5,000 Monte Carlo simulations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMean total treatment cost was 6,478 RMB (approximately 32 times estimated production cost), with a clinical cure rate of 68.2%. Median WTP was 13,543 RMB, yielding a mean consumer surplus of +\u0026thinsp;7,065 RMB. Critically, WTP exhibited strict \"zero income elasticity\": the coefficient of ln(income) was near zero and statistically insignificant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.9), indicating that psychological willingness to save a cat's life did not vary with owner income. Cat breed, age, and weight were also insignificant predictors of WTP. Interaction analysis confirmed this pattern across all city tiers, suggesting a \"decommodification\" of companion animal life in life-or-death decisions. PSA showed that at the median WTP threshold, the probability of black-market treatment being cost-effective was 98.3%. Nationally, estimated annual deadweight loss and negative externalities from this black market were approximately 59.8\u0026nbsp;million RMB and 48.9\u0026nbsp;million RMB, respectively.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWhile the black market for GS-441524 provides a clinical lifeline for cats with FIP, it imposes substantial social welfare losses through market failure. The finding of zero income elasticity reveals that in critical care decisions for companion animals, emotional bonds can transcend conventional budget constraints, leading to the \"decommodification\" of animal life. We recommend that authorities accelerate legal drug approval, implement cost-based pricing, and establish formal institutional mechanisms to replace informal compensation channels, thereby optimizing social welfare distribution.\u003c/p\u003e","manuscriptTitle":"Effective but Illegal: A Health Economics Analysis of the Black Market for GS-441524 in Treating Feline Infectious Peritonitis in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 07:16:31","doi":"10.21203/rs.3.rs-9116812/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ad05e008-5d64-4a00-b1cb-5a77b03bbf0c","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-27T01:09:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 07:16:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9116812","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9116812","identity":"rs-9116812","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}