Lyme Disease in Texas? Enhancing Prevention Through the Identfication of Areas of Risk

Presented by
Susan Swinson Williams

Transcript

1. Lyme  Disease  in  Texas?   Enhancing  Preven5on  Through  the   Iden5fica5on  of  Areas  of  Risk       Susan  Swinson  Williams     Penn  State  MGIS  Program   Advisor:  Dr.  Jus5ne  Blanford  
2. Outline   Overview   What  is  Lyme  disease?   Lyme  in  Texas   Objec5ves   Survey  Results   Methods   Risk  Mapping   Other  Poten5al  Applica5ons   Acknowledgements   Ques5ons  /  Comments  
3. Overview     •  Many  doctors  believe  that   “we  don’t  have  Lyme  in   Texas.”     •  Many  Texans  travel  out  of   state  for  diagnosis  and   treatment.   •  Preven?on  and  educa?on  are   the  best  approaches  against   Lyme  disease   •  Preven?on  and  educa?on   efforts  could  improve  if  we   determined  where  humans   may  be  at  greatest  risk  
4. What  is  Lyme  disease?   •  An  infec?on  caused  by  a  corkscrew-­‐shaped  spirochete  bacterium   •  Most  common  vector-­‐borne  disease  in  U.S.A.     •  TransmiGed  through  bite  of  an  infected  ?ck       Darkfield  microscopy  photomicrograph,  magnified   400x,  of  bacteria  Borrelia  burgdorferi  (CDC,  1993).   Dr.  Burgdorfer,  seen  here  inoculaDng  Dcks.  Credit:  NIAID/RML   Erythema  migrans  rash  (Source:  Wikipedia).    
5. •  Ticks  are  quite  small,  no  bigger   than  a  pinhead  in  the  larval  and   nymphal  stage     •  Their  size  enables  them  to  feed   on  hosts  unno?ced     •  Three  things  necessary  for  Lyme   transmission:     •  the  Lyme  bacteria,     •  the  ?cks  that  can  transmit  the   bacteria,     •  the  hosts  that  serve  as  a  meal   for  the  ?cks   Transmission  and  Distribu5on  
6. The  enzooDc  cycle  of  Borrelia  burgdorferi  (Source:  Radolph,  Caimano,  Stevenson,  &  Hu,  2012).   Transmission  and  Distribu5on  
7. Why  Does  Texas  Need  A  Risk  Map?   This  2012  ‘Risk  Map’  doesn’t  even  show  the  enDre  USA  nor  correlate   with  numbers  of  Lyme  disease  cases  reported  by  the  CDC.    We  can  do   beZer  than  this,  right?    (Yale  School  of  Public  Health,  2012)     The  few  maps  that  exist  on  this  subject  are  either   -­‐  Inaccurate  or  outdated     -­‐  not  very  specific     -­‐  or  all  of  the  above   The  CDC  admits  that  approx.  90%  of  cases  go  unreported,  so    these  figures  are    quite    a  bit   lower  than  reality.  (LDA,  2012)   Reported  Cases  1990-­‐2008  
8. Why  Does  Texas  Need  A  Risk  Map?   Approximate  distribuDon  of  three  vector  Dck  species  in  the  U.S.  (Source:  Bakken  et  al.,  2006).   Lyme  con?nues  to  spread  due  to  migratory  animals,  development,  reforesta?on,  and   climate  change.         Mul?ple  ?ck  species  exist  in  the  U.S.,  some  of   which  have  overlapping  distribu?ons.     Many  animals  serve  as  blood  hosts  for  feeding  Dcks.  (Source:  Levy,  2013)  
9. Lyme  Disease  in  Texas   •   Previous  research  indicated  that   1  to  4%  of  ?cks  tested  in  every   public  region  of  Texas  were   infected  with  Borrelia   burgdorferi  bacteria     (TXLDA,  2014).   •  Recent  research,  however,  found   Borrelia  infec?on  in  45%  of   Ixodes  ?cks  collected  from  20   coun?es  in  Texas  and  regions  of   northeastern  Mexico     (Feria-­‐Arroyo  et  al.,  2014).       •  Studies  have  demonstrated  that   the  Amblyomma  americanum   ?cks  can  and  do  carry  the   Borrelia  burgdorferi  bacteria       (Clark,  Leydet,  &  Threlkeld,  2014)    
10. •  Map  prevalence  of  Lyme  disease  in  Texas  by:   –  analyzing  known  distribu?on  of  reported  cases  in  Texas   –  survey  of  Texas  residents  with  Lyme  to  establish  human  incidence     –  Sta?s?cally  significant  areas  iden?fied  by  Exploratory  Spa?al  Data  Analysis   –  Created  an  updated  map  delinea?ng  the  current  extent  of  Lyme  incidence   in  Texas  based  on  reported  cases/survey.   Objec5ves   Iden?fy  poten?al  risk  areas   through  habitat  mapping  of     vector.   Provide  recommenda?ons.  
11.       Survey  Results   0%   10%   20%   30%   40%   50%   60%   70%   80%   No  Lyme   in  Texas   Chronic   Lyme   doesn't   exist   You’ve   had  30   days  of   an?bio?cs   Would  not   treat   Lyme   Referral  to   another   doctor   Other   73%   45%   20%   37%   16%   23%   Reasons  given  for  refusal  of  tes5ng   0%   5%   10%   15%   20%   25%   30%   35%   1   2  to  3   4  to  6   7  to  9   >  10     8%   18%   26%   15%   34%   Number  of  physicians  consulted   between  symptom  onset  diagnosis  
12.       Survey  Results   0%   10%   20%   30%   40%   50%   60%   59%   50%   30%   19%   39%   34%   8%   16%   Reasons  given  for  refusal  of  treatment   0%   5%   10%   15%   20%   25%   30%   35%   40%   45%   <  50  miles   51-­‐100  miles   101-­‐500   miles   Out  of  Texas   Out  of  the   U.S.   26%   11%   21%   42%   1%   Greatest  distance  traveled  for  Lyme   disease  treatment  
13.       Survey  Results   0%   10%   20%   30%   40%   50%   60%   70%   16%   4%   49%   21%   69%   39%   How  have  you  had  to  cut  down  or  limit   ac5vi5es  as  a  result  of  Lyme  disease?   0%   10%   20%   30%   40%   50%   60%   5%   6%   22%   15%   7%   1%   13%   24%   6%   How  did  addi5onal  abx  treatment   (>30  days)  affect  your  health?   Complete  Recovery   Much  BeGer   Somewhat  BeGer   Much  Worse   Somewhat  Worse   0%   20%   40%   60%   80%   YES   NO   I  don't  know   Other   13%   64%   19%   4%   Would  you  ever  consider  seeing  a   physician  who  follows  IDSA   guidelines  for  treatment?   0%   20%   40%   60%   80%   100%   YES   NO   Other  /  Unsure   2%   95%   3%   If  treated  by  IDSA  guidelines  ini5ally   (<  30  days  abx),  was  health  restored?    
15. Spa5al     Autocorrela5on  
16. Methods   Iden5fy  poten5al  risk  areas     through  habitat  mapping  of  the  vector   CLIMATIC  VARIABLES   VEGETATIVE  VARIABLES   Precipita?on   Vegeta?on  Type     (Na?onal  Land  Cover  Database)     Temperature  (Max  and  Min)   Soil  Type   (USDA  STATSGO  Database)   Normalized  Difference  Vegeta?on  Index  (NDVI)   (AVHRR  satellite  composites)      
17. Methods  –  the  NDVI   Normalized  Difference  Vegeta?on  Index  (NDVI)  =     a  ra?o  of  near-­‐infrared  (NIR)  to  red  light.       Healthy  or  dense  vegeta?on  =     high  posi?ve  NDVI     Unhealthy  or  less  dense  vegeta?on  =     lower  posi?ve  NDVI     Water  =  nega?ve  NDVI  
18. Reclassifica5on   Avg  Annual   Precipita5on   Average   Temperatures   NDVI  Values   NLCD  2006   Class  /  Value   Soils   0:  No  Poten5al   Risk   <  10  inches   <  -­‐10°C    and   >40.5°C                           (<  14°F)  (>104°F)   Nega?ve  values   (typically  open   water)   11:  Open  Water     All  dunes,  bare  rock   outcroppings,   badlands,  and  open   water   1:  Very  Low   Poten5al  Risk   10  –  20  inches   -­‐10°C  to  0°C       (14°F  to  32°F)   Very  Low  NDVI   values  (0.1  or  less)   31:  Barren  Land   (rock/sand/clay);   24:  Developed  High   Intensity;  90:   Woody  Wetlands   95:  Emergent  Herb.   Wetlands   acidic  soils  such  as   spodosols  and  clay-­‐ rich  soils  such  as   ul?sols  and  ver?sols;   Aridisols   2:  Low   Poten5al    Risk   20  –  30  inches   1°C  to  4°C                   (33°F  to  39°F)   Low  NDVI  Values   (0.2  to  0.3)   23:  Developed   Medium  Intensity;     81:  Pasture/Hay  ; 82:  Cul?vated   Crops   Histosols,  en?sols   3:  Medium   Poten5al  Risk   30  –  40  inches   35.5°C  to  40°C     (96°F  to  104°F)   Moderate  NDVI   Values  (0.4  to  0.5)   21:  Developed,   Open  Space;  22:   Developed,  Low   Intensity;  52:   Shrub/Scrub;  71:   Grassland/ Herbaceous   Incep?sols   4:  High   Poten5al    Risk   >  50  inches   4.4°C  to  35°C         (40°F  to  95°F)   High  NDVI  Values   (0.6  to  0.8)   42:  Evergreen   Forest  ;  43:  Mixed   Forest   Mollisols     5:  Very  High   Poten5al  Risk   40  –  50  inches   Very  High  NDVI   Values  (0.9  to  1.0)   41:  Deciduous   Forest   Alfisols  
19.       Risk  Mapping  
20.       Risk  Mapping  
21.       Risk  Mapping  
22. Risk  mapping  can  address  Lyme  in  other  neglected   regions  both  in  the  U.S.  (Virginia,  Georgia,  Louisiana)   and  other  na?ons  (Canada,  Mexico,  Caribbean,   Australia).     Similar  techniques  can  address  other  vector-­‐borne   diseases,  which  are  the  focus  of  the  World  Health   Organiza?on’s  2014  theme.         – 1,000,000+  die  from  VBD  per  year.  Many  more   are  let  with  chronic  illness  and  disabili?es  .     – 50%+  of  the  world’s  popula?on  is  at  risk.  Travel,   trade  and  migra?on  is  increasing  that  number.     – Diseases  also  a  serious  impediment  to  poverty   reduc?on  and  socioeconomic  development.       Other  Poten5al  Applica5ons  
23.         Acknowledgements   Special  thanks  to:       Dr.  Jus?ne  Blanford   Anna  E.  Berman         Phyllis  Shaw   Patricia  Ricks     The  Texas  Lyme  Disease  Associa?on  (TXLDA)   Texas  Natural  Resources  Informa?on  System  (TNRIS  )     Thank you for your attention today!
24. Ques5ons?   “It’s  ?ck  season   again!”