The 2023-2028 Outlook for Precision Medicines in China
This study covers the latent demand outlook for precision medicines across the regions of China, including provinces, autonomous regions (Guangxi, Nei Mongol, Ningxia, Xinjiang, Xizang - Tibet), municipalities (Beijing, Chongqing, Shanghai, and Tianjin), special administrative regions (Hong Kong and Macau), and Taiwan (all hereafter referred to as 'regions'). Latent demand (in millions of U.S. dollars), or potential industry earnings (P.I.E.) estimates are given across some 1,100 cities in China. For each major city in question, the percent share the city is of the region and of China is reported. Each major city is defined as an area of 'economic population', as opposed to the demographic population within a legal geographic boundary. For many cities, the economic population is much larger that the population within the city limits; this is especially true for the cities of the Western regions. For the coastal regions, cities which are close to other major cities or which represent, by themselves, a high percent of the regional population, actual city-level population is closer to the economic population (e.g. in Beijing). Based on this 'economic' definition of population, comparative benchmarks allow the reader to quickly gauge a city's marketing and distribution value vis-?-vis others. This exercise is quite useful for persons setting up distribution centers or sales force strategies. Using econometric models which project fundamental economic dynamics within each region and city of influence, latent demand estimates are created for precision medicines. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.
In this report we define the sales of precision medicines as including all commonly understood products falling within this broad category, irrespective of product packaging, formulation, size, or form. Companies participating in this industry include 23andMe, Ab-Biotics Sa, Abbott, Abcodia, ACS Biomarker, Actelion Pharmaceuticals, Advanced Biological Laboratories, Advaxis, Affymetrix, Agendia, Agenus, Alacer Corporation, Alberta Cancer Research Biobank, Alios BioPharma, Inc., Almac, Amgen, Apple, Archimedes, Aspen, Astellas Pharma, AstraZeneca, Astute Medical, Asuragen, AT&T, Athenahealth, Aurora, Auspex Pharmaceuticals, Avon Longitudinal Study of Parents and Children, Bayer, BGI Tech Solutions Company, Ltd., Biocrates Life Sciences, BioFortis, BioGene, Biomerieux, bioM?rieux, BioNTech, Bioven International Sdn Bhd, Bode Technology group, Inc., Bristol-Myers Squibb, CareWell Urgent Care, Caris, Celera Diagnostics, Cell & Co Biorepository, Celtics Healthcare, Cepheid, Cetics Healthcare Technologies Gmbh, CFR Pharmaceuticals, Ciba-Geigy, Clarient Diagnostic Services, Inc., Cognizant, Cooperative Human Tissue Network, Copan, Covance, Cubist Pharmaceuticals, CureVac, Daiichi Sankyo Company, Dako, Dell, Diabeter, Eagle Genomics, Ltd., Eli Lilly, Estonian Genome Project, F. Hoffmann-La Roche, Ferrer InCode, Ferring Pharmaceuticals, Fisher BioServices, Flakka, Foundation Medicine, GE Healthcare, Genome Medicine, Genomic Health, GenoSpace, Gen-Probe, GlaxoSmithKline, Glooko, Google, Gritstone Oncology, Hologic, Human Tissue Resource Network, HUNT Biobank, IBM, Idera Pharmaceuticals, Illumina, Immatics Biotechnologies, Immuneering Corporation, Immunovative Therapies, Infectio Diagnostic, Inc., Institutional Biobank of Lausanne, Intel, Intomics, Janssen Biotech, Japan Post Group, Johnson & Johnson, Kaiser Permanente, Lab-Ally, Laboratory Corporation of America, LG, Life Technologies, llumina, Luminex Molecular Diagnostics, Inc., Lutron Electronics, Mayo Clinic, Medpace, Medtronic, Merck, Moderna, Modul-Bio, Molecular Health, Monogram Bioscience, Myriad Genetic Laboratories, Nanosphere, NanoString, NantKwest, Neon Therapeutics, NextWave, Novartis, Omnyx, LLC, OncoMed Pharmaceuticals, Oncotype DX, OneMedNet Corporation, Oracle Healthcare, Panasonic Healthcare, PATH Biobank, Personalis, Pfizer, Philips Healthcare, ProMedDx, Q2 Solutions, Qiagen, Qualcomm, Quest Diagnostics, Randox Laboratories, Reddy Laboratories, Roche, Royal Philips, Samsung, Sandoz, Sanofi Aventis, Siemens Clinical Lab, Signature Diagnostics AG, St. Jude Medical (SJM), Sterand, PLC, Syapse, Sysmex, Takeda Pharmaceutical Company, Tepnel Pharma Services, Teva Pharmaceutical Industries, Therascreen, Thermo Fisher Scientific, Topera, Trofile, U.K. Biobank, UMass Cancer Center Tissue and Tumor Bank, Ventana Medical Systems, Veropharm, Vysis, and Zinfandel Pharmaceuticals. In addition to the sources indicated, additional information available to the public via news and/or press releases published by players in the industry was considered in defining and calibrating this category. All figures are in a common currency (U.S. dollars, millions) and are not adjusted for inflation (i.e., they are current values). Exchange rates used to convert to U.S. dollars are averages for the year in question. Future exchange rates are assumed to be constant in the future at the current level (the average of the year of this publication's release in 2022).
In this report we define the sales of precision medicines as including all commonly understood products falling within this broad category, irrespective of product packaging, formulation, size, or form. Companies participating in this industry include 23andMe, Ab-Biotics Sa, Abbott, Abcodia, ACS Biomarker, Actelion Pharmaceuticals, Advanced Biological Laboratories, Advaxis, Affymetrix, Agendia, Agenus, Alacer Corporation, Alberta Cancer Research Biobank, Alios BioPharma, Inc., Almac, Amgen, Apple, Archimedes, Aspen, Astellas Pharma, AstraZeneca, Astute Medical, Asuragen, AT&T, Athenahealth, Aurora, Auspex Pharmaceuticals, Avon Longitudinal Study of Parents and Children, Bayer, BGI Tech Solutions Company, Ltd., Biocrates Life Sciences, BioFortis, BioGene, Biomerieux, bioM?rieux, BioNTech, Bioven International Sdn Bhd, Bode Technology group, Inc., Bristol-Myers Squibb, CareWell Urgent Care, Caris, Celera Diagnostics, Cell & Co Biorepository, Celtics Healthcare, Cepheid, Cetics Healthcare Technologies Gmbh, CFR Pharmaceuticals, Ciba-Geigy, Clarient Diagnostic Services, Inc., Cognizant, Cooperative Human Tissue Network, Copan, Covance, Cubist Pharmaceuticals, CureVac, Daiichi Sankyo Company, Dako, Dell, Diabeter, Eagle Genomics, Ltd., Eli Lilly, Estonian Genome Project, F. Hoffmann-La Roche, Ferrer InCode, Ferring Pharmaceuticals, Fisher BioServices, Flakka, Foundation Medicine, GE Healthcare, Genome Medicine, Genomic Health, GenoSpace, Gen-Probe, GlaxoSmithKline, Glooko, Google, Gritstone Oncology, Hologic, Human Tissue Resource Network, HUNT Biobank, IBM, Idera Pharmaceuticals, Illumina, Immatics Biotechnologies, Immuneering Corporation, Immunovative Therapies, Infectio Diagnostic, Inc., Institutional Biobank of Lausanne, Intel, Intomics, Janssen Biotech, Japan Post Group, Johnson & Johnson, Kaiser Permanente, Lab-Ally, Laboratory Corporation of America, LG, Life Technologies, llumina, Luminex Molecular Diagnostics, Inc., Lutron Electronics, Mayo Clinic, Medpace, Medtronic, Merck, Moderna, Modul-Bio, Molecular Health, Monogram Bioscience, Myriad Genetic Laboratories, Nanosphere, NanoString, NantKwest, Neon Therapeutics, NextWave, Novartis, Omnyx, LLC, OncoMed Pharmaceuticals, Oncotype DX, OneMedNet Corporation, Oracle Healthcare, Panasonic Healthcare, PATH Biobank, Personalis, Pfizer, Philips Healthcare, ProMedDx, Q2 Solutions, Qiagen, Qualcomm, Quest Diagnostics, Randox Laboratories, Reddy Laboratories, Roche, Royal Philips, Samsung, Sandoz, Sanofi Aventis, Siemens Clinical Lab, Signature Diagnostics AG, St. Jude Medical (SJM), Sterand, PLC, Syapse, Sysmex, Takeda Pharmaceutical Company, Tepnel Pharma Services, Teva Pharmaceutical Industries, Therascreen, Thermo Fisher Scientific, Topera, Trofile, U.K. Biobank, UMass Cancer Center Tissue and Tumor Bank, Ventana Medical Systems, Veropharm, Vysis, and Zinfandel Pharmaceuticals. In addition to the sources indicated, additional information available to the public via news and/or press releases published by players in the industry was considered in defining and calibrating this category. All figures are in a common currency (U.S. dollars, millions) and are not adjusted for inflation (i.e., they are current values). Exchange rates used to convert to U.S. dollars are averages for the year in question. Future exchange rates are assumed to be constant in the future at the current level (the average of the year of this publication's release in 2022).
1 INTRODUCTION
1.1 OVERVIEW
1.2 WHAT IS LATENT DEMAND AND THE P.I.E.?
1.3 THE METHODOLOGY
1.3.1 STEP 1. PRODUCT DEFINITION AND DATA COLLECTION
1.3.2 STEP 2. FILTERING AND SMOOTHING
1.3.3 STEP 3. FILLING IN MISSING VALUES
1.3.4 STEP 4. VARYING PARAMETER, NON-LINEAR ESTIMATION
1.3.5 STEP 5. FIXED-PARAMETER LINEAR ESTIMATION
1.3.6 STEP 6. AGGREGATION AND BENCHMARKING
1.4 FREQUENTLY ASKED QUESTIONS (FAQ)
1.4.1 CATEGORY DEFINITION
1.4.2 UNITS
1.4.3 METHODOLOGY
2 SUMMARY OF FINDINGS
2.1 LATENT DEMAND IN CHINA
2.2 TOP 100 CITIES SORTED BY RANK
2.3 LATENT DEMAND BY YEAR IN CHINA
3 ANHUI
3.1 LATENT DEMAND BY YEAR - ANHUI
3.2 CITIES SORTED BY RANK - ANHUI
3.3 CITIES SORTED ALPHABETICALLY - ANHUI
4 BEIJING
4.1 LATENT DEMAND BY YEAR - BEIJING
4.2 CITIES SORTED BY RANK - BEIJING
4.3 CITIES SORTED ALPHABETICALLY - BEIJING
5 CHONGQING
5.1 LATENT DEMAND BY YEAR - CHONGQING
5.2 CITIES SORTED BY RANK - CHONGQING
5.3 CITIES SORTED ALPHABETICALLY - CHONGQING
6 FUJIAN
6.1 LATENT DEMAND BY YEAR - FUJIAN
6.2 CITIES SORTED BY RANK - FUJIAN
6.3 CITIES SORTED ALPHABETICALLY - FUJIAN
7 GANSU
7.1 LATENT DEMAND BY YEAR - GANSU
7.2 CITIES SORTED BY RANK - GANSU
7.3 CITIES SORTED ALPHABETICALLY - GANSU
8 GUANGDONG
8.1 LATENT DEMAND BY YEAR - GUANGDONG
8.2 CITIES SORTED BY RANK - GUANGDONG
8.3 CITIES SORTED ALPHABETICALLY - GUANGDONG
9 GUANGXI
9.1 LATENT DEMAND BY YEAR - GUANGXI
9.2 CITIES SORTED BY RANK - GUANGXI
9.3 CITIES SORTED ALPHABETICALLY - GUANGXI
10 GUIZHOU
10.1 LATENT DEMAND BY YEAR - GUIZHOU
10.2 CITIES SORTED BY RANK - GUIZHOU
10.3 CITIES SORTED ALPHABETICALLY - GUIZHOU
11 HAINAN
11.1 LATENT DEMAND BY YEAR - HAINAN
11.2 CITIES SORTED BY RANK - HAINAN
11.3 CITIES SORTED ALPHABETICALLY - HAINAN
12 HEBEI
12.1 LATENT DEMAND BY YEAR - HEBEI
12.2 CITIES SORTED BY RANK - HEBEI
12.3 CITIES SORTED ALPHABETICALLY - HEBEI
13 HEILONGJIANG
13.1 LATENT DEMAND BY YEAR - HEILONGJIANG
13.2 CITIES SORTED BY RANK - HEILONGJIANG
13.3 CITIES SORTED ALPHABETICALLY - HEILONGJIANG
14 HENAN
14.1 LATENT DEMAND BY YEAR - HENAN
14.2 CITIES SORTED BY RANK - HENAN
14.3 CITIES SORTED ALPHABETICALLY - HENAN
15 HONG KONG
15.1 LATENT DEMAND BY YEAR - HONG KONG
15.2 CITIES SORTED BY RANK - HONG KONG
15.3 CITIES SORTED ALPHABETICALLY - HONG KONG
16 HUBEI
16.1 LATENT DEMAND BY YEAR - HUBEI
16.2 CITIES SORTED BY RANK - HUBEI
16.3 CITIES SORTED ALPHABETICALLY - HUBEI
17 HUNAN
17.1 LATENT DEMAND BY YEAR - HUNAN
17.2 CITIES SORTED BY RANK - HUNAN
17.3 CITIES SORTED ALPHABETICALLY - HUNAN
18 JIANGSU
18.1 LATENT DEMAND BY YEAR - JIANGSU
18.2 CITIES SORTED BY RANK - JIANGSU
18.3 CITIES SORTED ALPHABETICALLY - JIANGSU
19 JIANGXI
19.1 LATENT DEMAND BY YEAR - JIANGXI
19.2 CITIES SORTED BY RANK - JIANGXI
19.3 CITIES SORTED ALPHABETICALLY - JIANGXI
20 JILIN
20.1 LATENT DEMAND BY YEAR - JILIN
20.2 CITIES SORTED BY RANK - JILIN
20.3 CITIES SORTED ALPHABETICALLY - JILIN
21 LIAONING
21.1 LATENT DEMAND BY YEAR - LIAONING
21.2 CITIES SORTED BY RANK - LIAONING
21.3 CITIES SORTED ALPHABETICALLY - LIAONING
22 MACAU
22.1 LATENT DEMAND BY YEAR - MACAU
22.2 CITIES SORTED BY RANK - MACAU
22.3 CITIES SORTED ALPHABETICALLY - MACAU
23 NEI MONGGOL
23.1 LATENT DEMAND BY YEAR - NEI MONGGOL
23.2 CITIES SORTED BY RANK - NEI MONGGOL
23.3 CITIES SORTED ALPHABETICALLY - NEI MONGGOL
24 NINGXIA
24.1 LATENT DEMAND BY YEAR - NINGXIA
24.2 CITIES SORTED BY RANK - NINGXIA
24.3 CITIES SORTED ALPHABETICALLY - NINGXIA
25 QINGHAI
25.1 LATENT DEMAND BY YEAR - QINGHAI
25.2 CITIES SORTED BY RANK - QINGHAI
25.3 CITIES SORTED ALPHABETICALLY - QINGHAI
26 SHAANXI
26.1 LATENT DEMAND BY YEAR - SHAANXI
26.2 CITIES SORTED BY RANK - SHAANXI
26.3 CITIES SORTED ALPHABETICALLY - SHAANXI
27 SHANDONG
27.1 LATENT DEMAND BY YEAR - SHANDONG
27.2 CITIES SORTED BY RANK - SHANDONG
27.3 CITIES SORTED ALPHABETICALLY - SHANDONG
28 SHANGHAI
28.1 LATENT DEMAND BY YEAR - SHANGHAI
28.2 CITIES SORTED BY RANK - SHANGHAI
28.3 CITIES SORTED ALPHABETICALLY - SHANGHAI
29 SHANXI
29.1 LATENT DEMAND BY YEAR - SHANXI
29.2 CITIES SORTED BY RANK - SHANXI
29.3 CITIES SORTED ALPHABETICALLY - SHANXI
30 SICHUAN
30.1 LATENT DEMAND BY YEAR - SICHUAN
30.2 CITIES SORTED BY RANK - SICHUAN
30.3 CITIES SORTED ALPHABETICALLY - SICHUAN
31 TAIWAN
31.1 LATENT DEMAND BY YEAR - TAIWAN
31.2 CITIES SORTED BY RANK - TAIWAN
31.3 CITIES SORTED ALPHABETICALLY - TAIWAN
32 TIANJIN
32.1 LATENT DEMAND BY YEAR - TIANJIN
32.2 CITIES SORTED BY RANK - TIANJIN
32.3 CITIES SORTED ALPHABETICALLY - TIANJIN
33 XINJIANG UYGUR
33.1 LATENT DEMAND BY YEAR - XINJIANG UYGUR
33.2 CITIES SORTED BY RANK - XINJIANG UYGUR
33.3 CITIES SORTED ALPHABETICALLY - XINJIANG UYGUR
34 XIZANG [TIBET]
34.1 LATENT DEMAND BY YEAR - XIZANG [TIBET]
34.2 CITIES SORTED BY RANK - XIZANG [TIBET]
34.3 CITIES SORTED ALPHABETICALLY - XIZANG [TIBET]
35 YUNNAN
35.1 LATENT DEMAND BY YEAR - YUNNAN
35.2 CITIES SORTED BY RANK - YUNNAN
35.3 CITIES SORTED ALPHABETICALLY - YUNNAN
36 ZHEJIANG
36.1 LATENT DEMAND BY YEAR - ZHEJIANG
36.2 CITIES SORTED BY RANK - ZHEJIANG
36.3 CITIES SORTED ALPHABETICALLY - ZHEJIANG
37 DISCLAIMERS, WARRANTIES, AND USER AGREEMENT PROVISIONS
37.1 DISCLAIMERS & SAFE HARBOR
37.2 ICON GROUP INTERNATIONAL, INC. USER AGREEMENT PROVISIONS
1.1 OVERVIEW
1.2 WHAT IS LATENT DEMAND AND THE P.I.E.?
1.3 THE METHODOLOGY
1.3.1 STEP 1. PRODUCT DEFINITION AND DATA COLLECTION
1.3.2 STEP 2. FILTERING AND SMOOTHING
1.3.3 STEP 3. FILLING IN MISSING VALUES
1.3.4 STEP 4. VARYING PARAMETER, NON-LINEAR ESTIMATION
1.3.5 STEP 5. FIXED-PARAMETER LINEAR ESTIMATION
1.3.6 STEP 6. AGGREGATION AND BENCHMARKING
1.4 FREQUENTLY ASKED QUESTIONS (FAQ)
1.4.1 CATEGORY DEFINITION
1.4.2 UNITS
1.4.3 METHODOLOGY
2 SUMMARY OF FINDINGS
2.1 LATENT DEMAND IN CHINA
2.2 TOP 100 CITIES SORTED BY RANK
2.3 LATENT DEMAND BY YEAR IN CHINA
3 ANHUI
3.1 LATENT DEMAND BY YEAR - ANHUI
3.2 CITIES SORTED BY RANK - ANHUI
3.3 CITIES SORTED ALPHABETICALLY - ANHUI
4 BEIJING
4.1 LATENT DEMAND BY YEAR - BEIJING
4.2 CITIES SORTED BY RANK - BEIJING
4.3 CITIES SORTED ALPHABETICALLY - BEIJING
5 CHONGQING
5.1 LATENT DEMAND BY YEAR - CHONGQING
5.2 CITIES SORTED BY RANK - CHONGQING
5.3 CITIES SORTED ALPHABETICALLY - CHONGQING
6 FUJIAN
6.1 LATENT DEMAND BY YEAR - FUJIAN
6.2 CITIES SORTED BY RANK - FUJIAN
6.3 CITIES SORTED ALPHABETICALLY - FUJIAN
7 GANSU
7.1 LATENT DEMAND BY YEAR - GANSU
7.2 CITIES SORTED BY RANK - GANSU
7.3 CITIES SORTED ALPHABETICALLY - GANSU
8 GUANGDONG
8.1 LATENT DEMAND BY YEAR - GUANGDONG
8.2 CITIES SORTED BY RANK - GUANGDONG
8.3 CITIES SORTED ALPHABETICALLY - GUANGDONG
9 GUANGXI
9.1 LATENT DEMAND BY YEAR - GUANGXI
9.2 CITIES SORTED BY RANK - GUANGXI
9.3 CITIES SORTED ALPHABETICALLY - GUANGXI
10 GUIZHOU
10.1 LATENT DEMAND BY YEAR - GUIZHOU
10.2 CITIES SORTED BY RANK - GUIZHOU
10.3 CITIES SORTED ALPHABETICALLY - GUIZHOU
11 HAINAN
11.1 LATENT DEMAND BY YEAR - HAINAN
11.2 CITIES SORTED BY RANK - HAINAN
11.3 CITIES SORTED ALPHABETICALLY - HAINAN
12 HEBEI
12.1 LATENT DEMAND BY YEAR - HEBEI
12.2 CITIES SORTED BY RANK - HEBEI
12.3 CITIES SORTED ALPHABETICALLY - HEBEI
13 HEILONGJIANG
13.1 LATENT DEMAND BY YEAR - HEILONGJIANG
13.2 CITIES SORTED BY RANK - HEILONGJIANG
13.3 CITIES SORTED ALPHABETICALLY - HEILONGJIANG
14 HENAN
14.1 LATENT DEMAND BY YEAR - HENAN
14.2 CITIES SORTED BY RANK - HENAN
14.3 CITIES SORTED ALPHABETICALLY - HENAN
15 HONG KONG
15.1 LATENT DEMAND BY YEAR - HONG KONG
15.2 CITIES SORTED BY RANK - HONG KONG
15.3 CITIES SORTED ALPHABETICALLY - HONG KONG
16 HUBEI
16.1 LATENT DEMAND BY YEAR - HUBEI
16.2 CITIES SORTED BY RANK - HUBEI
16.3 CITIES SORTED ALPHABETICALLY - HUBEI
17 HUNAN
17.1 LATENT DEMAND BY YEAR - HUNAN
17.2 CITIES SORTED BY RANK - HUNAN
17.3 CITIES SORTED ALPHABETICALLY - HUNAN
18 JIANGSU
18.1 LATENT DEMAND BY YEAR - JIANGSU
18.2 CITIES SORTED BY RANK - JIANGSU
18.3 CITIES SORTED ALPHABETICALLY - JIANGSU
19 JIANGXI
19.1 LATENT DEMAND BY YEAR - JIANGXI
19.2 CITIES SORTED BY RANK - JIANGXI
19.3 CITIES SORTED ALPHABETICALLY - JIANGXI
20 JILIN
20.1 LATENT DEMAND BY YEAR - JILIN
20.2 CITIES SORTED BY RANK - JILIN
20.3 CITIES SORTED ALPHABETICALLY - JILIN
21 LIAONING
21.1 LATENT DEMAND BY YEAR - LIAONING
21.2 CITIES SORTED BY RANK - LIAONING
21.3 CITIES SORTED ALPHABETICALLY - LIAONING
22 MACAU
22.1 LATENT DEMAND BY YEAR - MACAU
22.2 CITIES SORTED BY RANK - MACAU
22.3 CITIES SORTED ALPHABETICALLY - MACAU
23 NEI MONGGOL
23.1 LATENT DEMAND BY YEAR - NEI MONGGOL
23.2 CITIES SORTED BY RANK - NEI MONGGOL
23.3 CITIES SORTED ALPHABETICALLY - NEI MONGGOL
24 NINGXIA
24.1 LATENT DEMAND BY YEAR - NINGXIA
24.2 CITIES SORTED BY RANK - NINGXIA
24.3 CITIES SORTED ALPHABETICALLY - NINGXIA
25 QINGHAI
25.1 LATENT DEMAND BY YEAR - QINGHAI
25.2 CITIES SORTED BY RANK - QINGHAI
25.3 CITIES SORTED ALPHABETICALLY - QINGHAI
26 SHAANXI
26.1 LATENT DEMAND BY YEAR - SHAANXI
26.2 CITIES SORTED BY RANK - SHAANXI
26.3 CITIES SORTED ALPHABETICALLY - SHAANXI
27 SHANDONG
27.1 LATENT DEMAND BY YEAR - SHANDONG
27.2 CITIES SORTED BY RANK - SHANDONG
27.3 CITIES SORTED ALPHABETICALLY - SHANDONG
28 SHANGHAI
28.1 LATENT DEMAND BY YEAR - SHANGHAI
28.2 CITIES SORTED BY RANK - SHANGHAI
28.3 CITIES SORTED ALPHABETICALLY - SHANGHAI
29 SHANXI
29.1 LATENT DEMAND BY YEAR - SHANXI
29.2 CITIES SORTED BY RANK - SHANXI
29.3 CITIES SORTED ALPHABETICALLY - SHANXI
30 SICHUAN
30.1 LATENT DEMAND BY YEAR - SICHUAN
30.2 CITIES SORTED BY RANK - SICHUAN
30.3 CITIES SORTED ALPHABETICALLY - SICHUAN
31 TAIWAN
31.1 LATENT DEMAND BY YEAR - TAIWAN
31.2 CITIES SORTED BY RANK - TAIWAN
31.3 CITIES SORTED ALPHABETICALLY - TAIWAN
32 TIANJIN
32.1 LATENT DEMAND BY YEAR - TIANJIN
32.2 CITIES SORTED BY RANK - TIANJIN
32.3 CITIES SORTED ALPHABETICALLY - TIANJIN
33 XINJIANG UYGUR
33.1 LATENT DEMAND BY YEAR - XINJIANG UYGUR
33.2 CITIES SORTED BY RANK - XINJIANG UYGUR
33.3 CITIES SORTED ALPHABETICALLY - XINJIANG UYGUR
34 XIZANG [TIBET]
34.1 LATENT DEMAND BY YEAR - XIZANG [TIBET]
34.2 CITIES SORTED BY RANK - XIZANG [TIBET]
34.3 CITIES SORTED ALPHABETICALLY - XIZANG [TIBET]
35 YUNNAN
35.1 LATENT DEMAND BY YEAR - YUNNAN
35.2 CITIES SORTED BY RANK - YUNNAN
35.3 CITIES SORTED ALPHABETICALLY - YUNNAN
36 ZHEJIANG
36.1 LATENT DEMAND BY YEAR - ZHEJIANG
36.2 CITIES SORTED BY RANK - ZHEJIANG
36.3 CITIES SORTED ALPHABETICALLY - ZHEJIANG
37 DISCLAIMERS, WARRANTIES, AND USER AGREEMENT PROVISIONS
37.1 DISCLAIMERS & SAFE HARBOR
37.2 ICON GROUP INTERNATIONAL, INC. USER AGREEMENT PROVISIONS