Spatial Science Health data Issues Dr Mark Cresswell

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Spatial Science & Health data Issues Dr Mark Cresswell

Spatial Science & Health data Issues Dr Mark Cresswell

Topics o o o o Who compiles health data? Medical ethics Anonymised case records

Topics o o o o Who compiles health data? Medical ethics Anonymised case records Disease summary statistics Problems: human Problems: technical Examples of public-access health data

Who compiles Health Data? o General practitioners n o Hospitals n o o o

Who compiles Health Data? o General practitioners n o Hospitals n o o o Patient records Mortality, morbidity and rehabilitation Local health authorities National health ministry (NHS in UK) World Health Organization n Regional and World

UK Health Data o o o UK National Health Service was set up in

UK Health Data o o o UK National Health Service was set up in 1948 It is the largest organisation in Europe The NHS is funded by the taxpayer and managed by the Department of Health, which sets overall policy on health issues

NHS structure in England (Source: NHS, 2006)

NHS structure in England (Source: NHS, 2006)

Global Health Data? o World Health Organization (WHO) Established in 1948 n Based in

Global Health Data? o World Health Organization (WHO) Established in 1948 n Based in Geneva n Part of the United Nations Infrastructure n The attainment by all peoples of the highest possible level of health Health is defined in WHO's Constitution as a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.

Global Health Data? o The WHO is governed by 192 states which together make

Global Health Data? o The WHO is governed by 192 states which together make up the World Health Assembly o Main tasks for the assembly are to: Approve the WHO programme n Monitor and approve the WHO budget n Decide key policy issues n

WHO HQ in Geneva Goodwill Ambassadors Africa Americas General WHO Administrative Structure Europe E.

WHO HQ in Geneva Goodwill Ambassadors Africa Americas General WHO Administrative Structure Europe E. Mediterranean W Pacific S. E Asia

Who compiles Health Data? o Universities n n o o o Medical research Census

Who compiles Health Data? o Universities n n o o o Medical research Census and health economics Drug (pharmaceutical) companies NGOs (Médecins sans Frontières and IRC) Charitable donors (B&M Gates Foundation)

Who compiles Health Data? o Non Governmental Organisations may operate under special circumstances n

Who compiles Health Data? o Non Governmental Organisations may operate under special circumstances n Third World countries Areas affected by natural disasters or war Diseases and conditions poorly under resourced Action paid for by existing medical charities n Politics! n n n

Medical Ethics o o o Personal data must be regarded as strictly confidential at

Medical Ethics o o o Personal data must be regarded as strictly confidential at all times (GP data) Even today, data is transferred to/from hospitals by taxi (no digital system yet) UK Studies may use anonymised case data n n Unless drug trials Unless prior consent in focus study

Anonymised case records o o o Data may be released to scientific community for

Anonymised case records o o o Data may be released to scientific community for research purposes Personally identifiable portions of GP/hospital records is stripped out (name, address and maybe date of birth) Most records contain standard record information (age, sex, prior history, illness, duration of illness, location, date etc)

Disease Summary Statistics o o Specific diseases may be characterised by collating and summarising

Disease Summary Statistics o o Specific diseases may be characterised by collating and summarising case data Many diseases are grouped by theme and coded Medical statistics are employed to help analyse spatial and temporal change in disease Prevalence, morbidity, mortality etc are the common currency of epidemiologists

Disease Summary Statistics This is the number of new cases in a particular time

Disease Summary Statistics This is the number of new cases in a particular time period: INCIDENCE I = Incidence N = Number of new cases in a given time period P = Person years at risk during same time period Note that person years at risk means the total amount of time (in years) that each member of the population being studied (the study population) is at risk of the disease during the period of interest.

Disease Summary Statistics This is the proportion of current cases in a population at

Disease Summary Statistics This is the proportion of current cases in a population at a given point in time: PREVALENCE P = Prevalence Nc = Number of cases in the population at a given point in time P = Total population at the same point in time

Disease Summary Statistics The probability of having a disease, for those individuals who were

Disease Summary Statistics The probability of having a disease, for those individuals who were exposed to a risk factor. ABSOLUTE RISK Ra = Absolute Risk Ne = Number of cases of disease in those exposed Ie = Number of individuals exposed

Disease Summary Statistics This is an indication of the risk of developing a disease

Disease Summary Statistics This is an indication of the risk of developing a disease in a group of people who were exposed to a risk factor, relative to a group who were not exposed to it. RELATIVE RISK RR = Relative Risk Ie = Disease incidence in exposed group In = Disease incidence in non-exposed group

Problems: Human o Social inequality and marginalised people n o Taboo and embarrassment n

Problems: Human o Social inequality and marginalised people n o Taboo and embarrassment n o STDs and prostate/breast cancers Mis-diagnosis (poor equipment or training) n o poverty or caste/class/race divides Similarity of symptoms & no lab facilities Poor reporting or surveillance infrastructure

Problems: Human WHO vaccination campaign Burkina Faso Epidemiological Surveillance

Problems: Human WHO vaccination campaign Burkina Faso Epidemiological Surveillance

Problems: Technical o Diagnostics n n o Complex vector dynamics n o Time consuming

Problems: Technical o Diagnostics n n o Complex vector dynamics n o Time consuming Lab-on-chip technology expensive E. g. Bird flu (migratory patterns) Refugee and nomadic populations n n Use of satellites to track people Loss of medical records by displaced people

Saharan dust storm March 2004 (MODIS)

Saharan dust storm March 2004 (MODIS)

Disaster Monitoring Constellation (DMC) is a new series of geostationary satellites developed specifically for

Disaster Monitoring Constellation (DMC) is a new series of geostationary satellites developed specifically for disaster applications including health. DMC: 26 or 32 m resolution. Sunsynchronous A relatively cloud free image was available for the period 10: 12 GMT on 13/6/05. A water body was identified (LAT: 13. 054 N, LON: 2. 070 W). All three spectral channels (NIR, RED and GREEN) were sampled across a transect line bisecting the water body

Interpolation of sparse station readings is undesirable – so we must look to: •

Interpolation of sparse station readings is undesirable – so we must look to: • Remote sensing • Model output ABOVE: Model grid representation LEFT: Meteosat weather satellite

European health data o The WHO regional office for Europe provides access to country-specific

European health data o The WHO regional office for Europe provides access to country-specific health and disease statistics via the centralized information system for infectious diseases (CISID). This is available from http: //data. euro. who. int/cisid/. o Health for All database http: //www. euro. who. int/hfadb

European health data CISID data example

European health data CISID data example

European health data HFA data example

European health data HFA data example

African Malaria Data MARA data

African Malaria Data MARA data

African Malaria Data MARA data

African Malaria Data MARA data

African Malaria Data MARA data

African Malaria Data MARA data

African Malaria Data MARA data

African Malaria Data MARA data

African Meningitis Data MSF and MALSAT Spatial Distribution Meningitis Epidemics 1841 -1999 (n =

African Meningitis Data MSF and MALSAT Spatial Distribution Meningitis Epidemics 1841 -1999 (n = c. 425) 1 1 Molesworth A. M. , Thomson M. C. , Connor S. J. , Cresswell M. P. , Morse A. P. , Shears P. , Hart C. A. , Cuevas L. E. (2002) Where is the Meningitis Belt? , Transactions of the Royal Society of Hygiene and Tropical Medicine, 96, 242 -249.

WHO compile case statistics reports on a regular basis in a standard format

WHO compile case statistics reports on a regular basis in a standard format

WHO compile case statistics reports on a regular basis in a standard format

WHO compile case statistics reports on a regular basis in a standard format

WHO compile case statistics reports on a regular basis in a standard format

WHO compile case statistics reports on a regular basis in a standard format

ANY QUESTIONS

ANY QUESTIONS