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Pola Penyakit dan Distribusi. Outline Pendahuluan: Epidemiologi Penyakit Infeksi Pola Pengaruh Lingkungan Iklim sebagai Driver Lingkungan.

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Presentasi berjudul: "Pola Penyakit dan Distribusi. Outline Pendahuluan: Epidemiologi Penyakit Infeksi Pola Pengaruh Lingkungan Iklim sebagai Driver Lingkungan."— 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 Agent Host Environment Classical Epidemiological Triad

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

6 Environment Agent Host

7 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. Examples Involving Infectious Diseases

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

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

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

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

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

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

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

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

17

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

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

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

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

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

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

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

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

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

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

34 How can extensive time-space datasets help? T1T1 T2T2 T3T3 Pattern of disease … or knowledge, SES, exposure, etc...

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? Establishment and Colonization Dispersal, Invasion, Extinction, Reinvasion Inter-annual Fluctuations Time Abundance / Prevalence

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

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)


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