Comput Biol Chem - A state-time epidemiology model of tuberculosis: importance of re-infection.

Tópicos

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{ state(1844) use(1261) util(961) }
{ take(945) account(800) differ(722) }
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{ chang(1828) time(1643) increas(1301) }
{ inform(2794) health(2639) internet(1427) }
{ treatment(1704) effect(941) patient(846) }
{ method(1219) similar(1157) match(930) }
{ error(1145) method(1030) estim(1020) }
{ spatial(1525) area(1432) region(1030) }
{ patient(2837) hospit(1953) medic(668) }
{ high(1669) rate(1365) level(1280) }
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{ patient(1821) servic(1111) care(1106) }
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{ featur(3375) classif(2383) classifi(1994) }
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{ perform(1367) use(1326) method(1137) }
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{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
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{ ehr(2073) health(1662) electron(1139) }
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{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ drug(1928) target(777) effect(648) }
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Resumo

An epidemiological model is presented that considers five possible states of a population: susceptible (S), exposed (W), infectious (Y), in treatment (Z) and recovered (R). In certain instances transition rates (from one state to another) depend on the time spent in the state; therefore the states W, Y and Z depend on time and length of stay in that state - similar to age-structured models. The model is particularly amenable to describe delays of exposed persons to become infectious and re-infection of exposed persons. Other transitions that depend on state time include the case finding and diagnosis, increased death rate and treatment interruption. The mathematical model comprises of a set of partial differential and ordinary differential equations. Non-steady state solutions are first presented, followed by a bifurcation study of the stationary states.

Resumo Limpo

epidemiolog model present consid five possibl state popul suscept s expos w infecti y treatment z recov r certain instanc transit rate one state anoth depend time spent state therefor state w y z depend time length stay state similar agestructur model model particular amen describ delay expos person becom infecti reinfect expos person transit depend state time includ case find diagnosi increas death rate treatment interrupt mathemat model compris set partial differenti ordinari differenti equat nonsteadi state solut first present follow bifurc studi stationari state

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