Calculation of patient
number in Africa*
Rare Indication Calculated patient
No.
Musculoskeletal: 7,700,000
Cardiovascular: 450,000
Respiratory: 760,000
Endocrine: 3,400,000
Gastro/Hepatic/Renal: 3,600,000
Developmental/
in born metab: 39,880,000
Immune/immunodeficiency: 5,400,000
Infectious: 2,400,000
Neuro/neuromuscular*: 11,800,000
Dermatological: 6,100,000
Hematological: 2,200,000
Neoplastic/Tumor**: 5,100,000
Opthalmic: 1,200,000
Toxic/environment induced: 300,000
​​
Total 90,290,000
​​
*incl. epilepsies and mobility disorders
** Excluding those on the Global Cancer Observatory database
as a main cancer class, or a subtype of that cancer
​
The Impacts
Medical Costs: 15x higher in patients with rare diseases
​
Patients with rare diseases can have total healthcare costs upto 15x higher than non-rare disease patients, with a significant part of that due to unnecessary hospital visits and treatments (ref 1).
​
But early diagnosis and treatment can reduce these by upto 41% (ref 2).
​
Personal Costs: can reach up to $500,000
​
Personal healthcare burden and costs can reach up to 2-years of a families total income over 10 years, while economic and social productivity costs impact the patient & their caregiver, reaching upto $500,000 (refs 3,4).
​
Absence of treatment solutions: target commonalities
​​
The absence of targeted treatments, often means practitioners are reluctant to enter into the diagnostic process, however very early diagnosis may facilitate tackling many diseases at a time by focusing on commonalities (refs 1,5)
A Global 'Universal Healthcare' marketplace will
change everything
By 2030,
UN member states have unanimously agreed to
​
Universal Healthcare Coverage for people living with rare diseases
(UN resolution 76/132 : ref 6)
If you can detect and facilitate the early diagnosis of the patients and positioning on a care pathway
& permit product use, globally, providing standards are adhered to
​​
​
Innovation risk for designed & targeted approaches for rare diseases
​
can be reduced and investment enabled
*How we performed the epidemiological analysis
There are publicly available databases on rare disease epidemiology. The French government and the European Union created https://www.orphadata.com , curated byOrphanet: https://www.orpha.net/ which represents one of the longest standing and most respected open sources of global information on rare diseases; its databases are peer reviewed and routinely updated.
Epidemiological data can be acceesed, and they have epidemiological data for approximately 6,000 of the 10,000 known rare diseases.
​
Orphanet range (patients/people ) Value we used
<1/1,000,000 0,001/1,000,000
1-9/1,000,000 people 1/1,000,000
10-90/1,000,000 10/1,000,000
100-500/1,000,000 100/1,000,000
600-900/1,000,000 people 300/1,000,000
Epidemiological data is presented in ranges, for which we used the lowest and most stringent value to apply to our analysis, and then applied these values across the 1,373 million people that live in Africa across all indications with a reported epidemiology*
​
​​*it is important to state that epidemiological data was mainly created from non-African locations but extrapolations can be made.
References
1 Chiesi. 2023. Rare disease burden of care and the economic impact on citizens. Sourced from: https://chiesirarediseases.com/assets/pdf/pp-g-1337-rare-disease-burden-of-care-and-the-economic-impact-on-citizens.pdf
2 Chung, Claudia C.Y. et al. The Lancet Regional Health – Western Pacific, Volume 34, 100711, 2024
3 Parikh R, et al . Proc (Bayl Univ Med Cent). 2016 Apr;29(2):212-3.
4 The Cost of Delayed Diagnosis in Rare Disease: A Health Economic Study. Sourced from https://everylifefoundation.org
5 NCATS, January 2023. Delivering hope for rare diseases. Accessed from https://ncats.nih.gov/sites/default/files/NCATS_RareDiseasesFactSheet.pdf
6 United Nations 2021. Resolution A/RES/76/132. Accessed from https://digitallibrary.un.org/record/3953832?ln=en