Pola Penyakit dan Distribusi

Presentasi berjudul: "Pola Penyakit dan Distribusi"— Transcript presentasi:

1 Pola Penyakit dan Distribusi

2 Outline Pendahuluan: Epidemiologi Penyakit Infeksi
Pola Pengaruh Lingkungan Iklim sebagai Driver Lingkungan

3 Climate Variability vs. Climate Change
Perubahan Iklim: - Terus-menerus mengubah atau tren dalam kondisi atmosfer berarti - Perubahan saat ini belum pernah terjadi sebelumnya dalam sejarah manusia Variabilitas Iklim: - Sehari-hari (cuaca) atau relatif jangka pendek (musiman) perubahan kondisi atmosfer - Efek pada pola penyakit yang paling mudah dianalisis, dan digunakan dalam prakiraan

4 Classical Epidemiological Triad
Environment Agent Host

5 Environment* Agent Host
(biophysical, psycho-social, etc.) Agent (diverse exposures, including non-contagious ) Host (animal, plant, ultimately human) *CLIMATE is an Environmental Influence

6 Environment Agent Host

7 longevity & infectivity
Examples Involving Infectious Diseases Environment host distribution, abundance, infection longevity & infectivity outside host e.g. cholera hantaviral disease hookworm schistosomiasis Agent nutrition treatment e.g. TB, HIV/AIDS, diarrheal diseases, acute respiratory infections housing hygiene Host tissue tropisms, pathogenicity, immune response, host specificity e.g. rabies, Lyme disease, malaria, cryptosporidiosi.

8 But for ALL diseases, complex interactions occur...
Agent Host Environment Altered hygiene Redesigned housing Better nutrition Improved irrigation

9 New antibiotics, pesticides
Environment Agent transport to new areas New antibiotics, pesticides Labor actions affecting toxin exposure Agent Host

10 Environment Agent Host Exposure probability, host immunity,
support networks, availability of supportive care Agent Host

11 Examples of Environmental and Epidemiological Data
Iklim pola - variabilitas ... mungkin berubah ... Tata Guna Tanah / Pola Tanah Data kasus pada Manusia kasus data (tertentu atau sindromik) Kelimpahan vektor dan infeksi patogen Kelimpahan Reservoir / prevalensi infeksi Lingkungan penggunaan dan eksposur Pembangunan ekonomi, demografi manusia, migrasi ... Each of these is historically changing in time and space

12 Social and Economic Policies
Environmental Determinants of Human Disease Social and Economic Policies Institutions (including medical care) Living Conditions Social Relationships Individual Risk Factors Genetic/Constitutional Factors Physical Environment Pathophysiologic pathways Individual/Population Health Modified from Kaplan, 2002

13 Climate? Social and Economic Policies
Research Challenge – Analyze and understand interactions! Social and Economic Policies Institutions (including medical care) Living Conditions Social Relationships Individual Risk Factors Genetic/Constitutional Factors Pathophysiologic pathways Individual/Population Health Climate?

14 What is climate change? Climate variability?
High Unchanging Average, Unchanging Extremes Environmental Variable Average Trend (solid line) Actual Measure (dashed line) Low Time

15 Environmental Variable
High Unchanging Average, Increasing Extremes Environmental Variable Average Trend (solid line) Actual Measure (dashed line) Low Time

16 Environmental Variable
High Increasing Average, Unchanging Extremes Environmental Variable Average Trend (solid line) Actual Measure (dashed line) Low Time

17

18 Environmental Variable
High Increasing Average, Greater Extremes Environmental Variable Average Trend (solid line) Actual Measure (dashed line) Low Time

19 Environmental Variable
High Increasing Rate of Increasing Average, Unchanging Extremes Environmental Variable Average Trend (solid line) Actual Measure (dashed line) Low Time

20 Environmental Variable
High Increasing Rate of Increasing Average, Greater Extremes Environmental Variable Average Trend (solid line) Actual Measure (dashed line) Low Time

21 Masing-masing pola perubahan iklim mungkin memiliki dampak berbeda pada risiko penyakit tertentu. Efek akan tergantung pada ekologi transmisi dan etiologi penyakit dan ekspresi.

22 Each exposure type should be considered in context of:
PERSON (age, behavior, gender, SES, etc.) TIME (year, season, adjacent periods, etc.) PLACE (geographic location, habitat, proximity, etc.) Most Epidemiological studies only superficially consider this for environmental (climatic) exposures: PERSON most often involves standard descriptors that do not include "social" characteristics or other environmental exposures (e.g. climatic). TIME is rarely dynamic, considers only recent past, and climate pattern over long periods not always available. PLACE often ignored or not carefully evaluated (e.g. spatial autocorrelation, climate patterns in regions may be important ).

23 Environment and Exposure
Direct Exposure Indirect Exposure Environmental Exposures Source Humans Solar UV EM Radiation Tetanus Vehicle Humans Source Stream pollutants Air Particulates Legionella Anthroponotic Infections Humans STDs Measles Hepatitis B Vehicle Humans Malaria Dengue Roundworm Zoonotic Infections Animals Humans Anthrax Ebola (?) CJD Vehicle Animals Humans Lyme Disease Hantaviral Disease Most arboviral diseases

24 Environment and Exposure Where might Climate Impact?
Direct Exposure Indirect Exposure Environmental Exposures Source Humans Solar UV EM Radiation Tetanus Vehicle Humans Source Stream pollutants Air Particulates Legionella

25 Environment and Exposure Where might Climate Impact?
Direct Exposure Indirect Exposure Anthroponotic Infections Humans STDs Measles Hepatitis B Vehicle Humans Malaria Dengue Roundworm

26 Environment and Exposure Where might Climate Impact?
Direct Exposure Indirect Exposure Zoonotic Infections Animals Humans Anthrax Ebola (?) CJD Vehicle Animals Humans Lyme Disease Hantaviral Disease Most arboviral diseases

27 Elements of Climate and Health
Heat-related mortality Extreme Events Air Pollution Vector-borne Diseases Water-borne Diseases Agricultural Production Maximum Temperature Minimum Temperature Mean Temperature Rainfall Amount Rainfall Frequency Rainfall Rate

28 What diseases are climate sensitive?
More sensitive Which are more sensitive???? High Moderate Sensitivity Less sensitive What about less sensitive??? Low Lowest Sensitivity

29 What diseases are climate sensitive?
More sensitive heat stress effects of storms air pollution effects asthma vector-borne diseases water-borne diseases food-borne diseases High Moderate Sensitivity Less sensitive sexually transmitted diseases violence most cancers atherosclerosis tuberculosis myocardial infarction Low Lowest Sensitivity

30 More Climate Sensitive
Sexually transmitted Disease Heat stress Effects of Storms Water-borne disease More Complex Food-borne disease Asthma Atherosclerosis Vector-borne Disease Cancer (not skin) Myocardial Infarction Violence More Climate Sensitive

31 Diskusi ... Dari PENGALAMAN ANDA atau KESUKAAN: Penyakit apa yang mungkin memiliki link dengan iklim dan variabel apa yang mungkin berdampak pada iklim yang berpengaruh pada penyakit? MENGAPA? Apa jalur biologis atau sosial? Bagaimana ini diselidiki / diteliti? Apa informasi tambahan yang akan Anda cari? Bagaimana Anda mengintegrasikan ini menjadi penentu risiko LAIN? Bisakah Anda perkiraan risiko berdasarkan analisis ini sendirian? Apa faktor lain harus dipertimbangkan dan mengapa?

32 Pentingnya temporal dan spasial data luas dalam menganalisis dan menafsirkan peran iklim: Perubahan iklim yang terjadi selama periode waktu yang lama variabilitas perubahan iklim tidak mudah untuk mengakui tanpa pengamatan jangka panjang Ruang-waktu perubahan pola penyakit memerlukan pengawasan yang akurat dan konsisten (sering tidak ada, terutama di negara-negara berkembang) Inferensi link iklim-penyakit terbatas tanpa seksama dengan mempertimbangkan pola ruang-waktu

33 Interpreting Spatial Patterns of Risk
b Area of risk Size of areas Location and pattern Inter-area distances Connectivity among locations c d

34 How can extensive time-space datasets help?
Pattern of disease … or knowledge, SES, exposure, etc... T1 T2 T3

35 How can extensive time-space datasets help?

36 How can extensive temporal datasets help?
Time Abundance / Prevalence

37 How can extensive temporal datasets help?
Time Abundance / Prevalence Establishment and Colonization Dispersal, Invasion, Extinction, Reinvasion Inter-annual Fluctuations

38 How can extensive spatial datasets help?
High Habitat Fragmentation Climate variable Change in Suitable Habitat Distance from Source Abundance or Infection Low Environmental Index Low High

39 Some Sources of Data Meteorological Stations (climate, weather)
Satellite – climate, vegetation, soil moisture, etc Census: population, age, sex, location, etc… Passive or active surveillance of human cases Surveillance of vector, reservoir abundance more...

40 Knowing is not enough; we must apply. Willing is not enough; we must do. (Goethe)