Cryptosporidium is a microscopic parasite (Apicomplexan oocyst-forming protozoan) that causes the diarrhoeal disease cryptosporidiosis. Both the parasite and the disease are also known as "Crypto."
There are ~20 different species of Cryptosporidium; however the main two species that infect humans are C. hominis and C. parvum (also found in bovines). Other species that have been found to infect humans, but are rarer, include C. meleagridis, C. felis, C. canis, C. andersoni, C. suis, C. baylei and C. muris. Within each species, multiple sub-types exist (e.g. Ia, Ib etc).
This report provides the current incident population for Cryptosporidium across Selected Asian Markets (Cambodia, Indonesia, Lao PDR, and Viet Nam) split by gender and 5-year age cohort. Along with the current incidence, the report also contains a disease overview of the risk factors, disease diagnosis and prognosis along with specific variations by geography and ethnicity.
Providing a value-added level of insight from our analysis team, several of the main symptoms of Cryptosporidium have been quantified and presented alongside the overall incidence figures. These sub-populations within the main disease are also included at a country level across the 10-year forecast snapshot.
Crypto occurs worldwide, although there are certain factors which can increase its likelihood. These include:
• Sanitation levels & source of drinking water
• Cohabitation with infected animals
• Age
• Immune status
This report is built using data and information sourced from the proprietary Epiomic patient segmentation database. To generate accurate patient population estimates, the Epiomic database utilises a combination of several world class sources that deliver the most up to date information from patient registries, clinical trials and epidemiology studies. All of the sources used to generate the data and analysis have been identified in the report.
Reason to buy
• Able to quantify patient populations in global Cryptosporidium’s market to target the development of future products, pricing strategies and launch plans.
• Gain further insight into the incidence of the subdivided types of Cryptosporidium and identify patient segments with high potential.
• Delivery of more accurate information for clinical trials in study sizing and realistic patient recruitment for various countries.
• Identify sub-populations within Cryptosporidium which require treatment.
• Gain an understanding of the specific markets that have the largest number of Cryptosporidium patients.
'
Table of Contents
• List of Tables and Figures
• Introduction
• Cause of the Disease
• Risk Factors & Prevention
• Diagnosis of the Disease
• Variation by Geography
• Disease Prognosis & Clinical Course
• Methodology for quantification of patient numbers
• Top-line Estimated Incidence for Cryptosporidium
• Cryptosporidium in Vietnam
o Distribution by Province within the Red River Delta Area
o Distribution by Province within the North Central & Central Coastal Areas
• Abbreviations used in the report
• Other Black Swan Analysis Publications
• Black Swan Analysis Online Patient-Based Databases
• Patient-Based Offering
• Online Pricing Data and Platforms
• References
• Appendix
List of Figures
• Scaling method schematic for estimating total caseload of cryptosporidium from diarrhoea cases in country
List of Tables
• Estimated incidence of Cryptosporidium, total (000s)
• Estimated likely symptomatic cases of Cryptosporidium, total (000s)
• Estimated caseload likely seeking treatment for Cryptosporidium, total (000s)
• Cryptosporidium estimated caseload in Viet Nam by region, total (000s)
• Cryptosporidium estimated caseload in Red River Delta by Province, total (000s)
• Cryptosporidium estimated caseload in the North Central / Central Coastal areas by Province, total (000s)
• Abbreviations and Acronyms used in the report
• Cambodia Estimated Incidence of Cryptosporidium (median projection) by 5-yr age cohort, total (000s)
• Cambodia Estimated Incidence of Cryptosporidium (low projection) by 5-yr age cohort, total (000s)
• Cambodia Estimated Incidence of Cryptosporidium (high projection) by 5-yr age cohort, total (000s)
• Indonesia Estimated Incidence of Cryptosporidium (median projection) by 5-yr age cohort, total (000s)
• Indonesia Estimated Incidence of Cryptosporidium (low projection) by 5-yr age cohort, total (000s)
• Indonesia Estimated Incidence of Cryptosporidium (high projection) by 5-yr age cohort, total (000s)
• Lao PDR Estimated Incidence of Cryptosporidium (median projection) by 5-yr age cohort, total (000s)
• Lao PDR Estimated Incidence of Cryptosporidium (low projection) by 5-yr age cohort, total (000s)
• Lao PDR Estimated Incidence of Cryptosporidium (high projection) by 5-yr age cohort, total (000s)
• Viet Nam Estimated Incidence of Cryptosporidium (median projection) by 5-yr age cohort, total (000s)
• Viet Nam Estimated Incidence of Cryptosporidium (low projection) by 5-yr age cohort, total (000s)
• Viet Nam Estimated Incidence of Cryptosporidium (high projection) by 5-yr age cohort, total (000s)
• Cambodia Population (median projection variant) by 5-yr age cohort, males (000s)
• Cambodia Population (median projection variant) by 5-yr age cohort, females (000s)
• Indonesia Population (median projection variant) by 5-yr age cohort, males (000s)
• Indonesia Population (median projection variant) by 5-yr age cohort, females (000s)
• Lao, PDR Population (median projection variant) by 5-yr age cohort, males (000s)
• Lao, PDR Population (median projection variant) by 5-yr age cohort, females (000s)
• Viet Nam Population (median projection variant) by 5-yr age cohort, males (000s)
• Viet Nam Population (median projection variant) by 5-yr age cohort, females (000s)
