Epiomic Epidemiology Series: Cryptosporidium Forecast for selected Asian Markets 2017-2027

December 2016 | 40 pages | ID: EE5DF42B143EN
Black Swan Analysis limited

Abstracts

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 the analysis team at Black Swan, 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.

Contents

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
  Distribution by Province within the Red River Delta Area
  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

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)