Spat Spatiotemporal Epidemiol - The spatial epidemiologic (r)evolution: a look back in time and forward to the future.

Tópicos

{ spatial(1525) area(1432) region(1030) }
{ data(2317) use(1299) case(1017) }
{ algorithm(1844) comput(1787) effici(935) }
{ howev(809) still(633) remain(590) }
{ system(1976) rule(880) can(841) }
{ data(1714) softwar(1251) tool(1186) }
{ risk(3053) factor(974) diseas(938) }
{ treatment(1704) effect(941) patient(846) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ import(1318) role(1303) understand(862) }
{ activ(1138) subject(705) human(624) }
{ data(1737) use(1416) pattern(1282) }
{ imag(1057) registr(996) error(939) }
{ care(1570) inform(1187) nurs(1089) }
{ model(2656) set(1616) predict(1553) }
{ cost(1906) reduc(1198) effect(832) }
{ analysi(2126) use(1163) compon(1037) }
{ implement(1333) system(1263) develop(1122) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ method(1557) propos(1049) approach(1037) }
{ design(1359) user(1324) use(1319) }
{ general(901) number(790) one(736) }
{ search(2224) databas(1162) retriev(909) }
{ system(1050) medic(1026) inform(1018) }
{ visual(1396) interact(850) tool(830) }
{ perform(1367) use(1326) method(1137) }
{ record(1888) medic(1808) patient(1693) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ intervent(3218) particip(2042) group(1664) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ survey(1388) particip(1329) question(1065) }
{ decis(3086) make(1611) patient(1517) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ bind(1733) structur(1185) ligand(1036) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ model(2341) predict(2261) use(1141) }
{ compound(1573) activ(1297) structur(1058) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

Spatial epidemiology enables you to better understand diseases or ill-health processes; investigate relationships between the environment and the presence of disease; conduct disease cluster analyses; predict disease spread; evaluate control alternatives; and basically do things an epidemiologist otherwise would have been unable to do and avoid many errors that otherwise may have been committed. Recently, the discipline of spatial epidemiology has advanced substantially, owing to a combination of reasons. The introduction of the electronic computer has clearly led this advancement. Computers have facilitated the storage, management, display and analysis of data, which are critical to geographic information systems (GIS). Also, because of computers and their increased capabilities and capacities, data collection has greatly expanded and reached a new level owing in large part to the advent of geographic positioning systems (GPS). GPS enables the collection of spatial locations, which in turn present yet another attribute (location) amenable to consideration in epidemiologic studies. At the same time, spatial software has taken advantage of the evolution of computers and data, further enabling epidemiologists to perform spatial analyses that they may not have even conceived of 30 years before. Capitalizing on these now, non-binding technologic constraints, epidemiologists are more able to combine their analytic expertise with computational advances, to develop approaches, which enable them to make spatial epidemiologic methods an integral part of their toolkits. Instead of a novelty, spatial epidemiology is now more of a necessity for outbreak investigations, surveillance, hypothesis testing, and generating follow-up activities necessary to perform a complete and proper epidemiologic analysis.

Resumo Limpo

spatial epidemiolog enabl better understand diseas illhealth process investig relationship environ presenc diseas conduct diseas cluster analys predict diseas spread evalu control altern basic thing epidemiologist otherwis unabl avoid mani error otherwis may commit recent disciplin spatial epidemiolog advanc substanti owe combin reason introduct electron comput clear led advanc comput facilit storag manag display analysi data critic geograph inform system gis also comput increas capabl capac data collect great expand reach new level owe larg part advent geograph posit system gps gps enabl collect spatial locat turn present yet anoth attribut locat amen consider epidemiolog studi time spatial softwar taken advantag evolut comput data enabl epidemiologist perform spatial analys may even conceiv year capit now nonbind technolog constraint epidemiologist abl combin analyt expertis comput advanc develop approach enabl make spatial epidemiolog method integr part toolkit instead novelti spatial epidemiolog now necess outbreak investig surveil hypothesi test generat followup activ necessari perform complet proper epidemiolog analysi

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