A Predictive Model on the Spread of the HIV Virus in Cebu City By Jose D. Velez, Jr.
Abstract:
Among Philippine cities, Manila made It for several years to the U list of cities !ith high incidence of "IV infections. #ately, ho!ever, $e%& $ity o&tran 'ed Manila. (ith the U goal to end the AID) epidemic %y *++, $e%& $ity-s case is alarming. he pro%lem needs immediate attention. (itho&t any form of intervention, the infection rate is %o&nd to rise f&rther. o sim&late !hat !o&ld %e the AID) scenario sans any intervention, a predictive model on the spread of the "IV vir&s is made &sing data from the University of the Philippines Pop&lation Instit&te. In *+/+, the University of the Philippines came &p !ith a comparative st&dy on the lifestyle and health of call center agents in Metro Manila and Metro $e%&. Among the data gathered !ere those of ris'y lifestyle of BP0 agents in $e%& that co&ld ma'e them v&lnera%le to infection. his paper designs a predictive model on the spread of the "IV vir&s %y the year *+*+ to ill&strate the pro%a%le e1tent of infection if the trend contin&es.
Keywords:$e%& $ity, BP0, Philippines, UAID)
I. I!"#$%C!I#
he Joint United ations Programme on "IV and AID) 2UAID)3, the U %ody tas'ed to ma1imize res<s for the glo%al AID) response hopes to end the AIDs epidemic %y the year *++. D&%%ed 4ast rac' *++, UAID) foc&ses its campaigns in di5erent cities thro&gho&t the !orld. he reason for this is the o%servation that 6t!o of the most dramatic events the past t!o decades have converged in cities7 the astonishing gro!th of cities themselves ... and the glo%al AID) epidemic8 2UAID), *+/93. Manila in the Philippines made it to the list of cities %eing monitored %y the glo%al %ody since for several years no!: it is the Philippine city !ith the most n&m%er of "IV infections. "o!ever, in J&ne *+/;, the Department of "ealth 2D0"3
(hile cities s&ch as Bang'o', e! >or', Paris and Vanco&ver have s&ccessf&lly red&ced "IV transmissions 2UAID), *+/93 $e%&-s "IV infection has %een accelerating. According to the D0"
0f great help to this paper is a comparative st&dy made %y the University of the Philippines Pop&lation Instit&te in *+/+ titled, 6#ifestyle, "ealth )tat&s and Behavior of >o&ng (or'ers in $all $enters and 0ther Ind&stries7 Metro Manila and Metro $e%&. he said st&dy doc&mented the lifestyle, health, se1&al practices, and a!areness of the AID) disease, among others of BP0 !or'ers in Metro Manila and Metro $e%&. Data on $e%& call center agents gathered %y researches of the said st&dy !ere singled o&t and tapped to ma'e the sim&lation. hey shed light on the c&rrent highris' lifestyle and %ehavior of call center agents !hich ma'e them v&lnera%le to "IV infection.
he history of the AID) epidemic reveals some important facts regarding the spread of the disease !hich can %e &sef&l in addressing the $e%& "IV and AID) sit&ation.
In a s&rvey involving Americans title d, "ighris' )e1&al
Behavior in the Feneral Pop&lation 2
million have had ; or more se1&al partner in the past yearH and . million have had se1 !ith a strangerH "igher n&m%er of se1&al partners, %oth recently and totally, is associated !ith increased ris' for a n&m%er of %acterial infections H It also poses a greater c&m&lative ris' for acG&iring viral infections, s&ch as general herpes, h&man papillomavir&s, hepatitis B and "IVH8 2Anderson and Dahl%erg, /EE*3. (ith the recent report of D0" = placing $e%& in the ?rst place among cities !ith high "IV infections, it is pressing to assess once again the ris's factors involving the general pop&lation, foc&sing this time on the pro%a%le spread of the "IV vir&s among BP0 !or'ers. BP0 !or'ers are of concern to this st&dy as most of them share a common high ris' lifestyle and are prone to get infected %y the vir&s. o e1plore the pro%a%le spread of the disease, and to %ring attention to the AID) sit&ation in $e%&, this st&dy comes &p !ith a predictive agent%ased model &sing the data from the UP st&dy. his paper presents !hat the AID) and "IV scenario !ill %e among call center agents In $e%& %y the year *+*+.
&. ASS%MP!I#S
CC men and =* !omen from vario&s BP0 companies agreed to %e made the respondents in the UP st&dy 2UP Pop&lation Instit&te, *++E3. "o!ever, the response rate varies and is lo! for some G&estions.
he sim&lation in this st&dy relies on the follo!ing ass&mptions !hich are themselves %ased on the data gathered %y the UP st&dy.
'.(. Se)ual *ehavior
/+ call center agents in $e%& !ho are less than ; years old !ere s&rveyed in *++E and as'ed on their se1&al practices the past /* months prior to thes&rvey. CC men and =* !ome n !ere mad e the respondents. follo!ing ass&mptions can %e made7
Based on the UP st& dy, the
Male call center agents tend to engage more in ris'y se1&al %ehavior compared to their female co&nterparts. he UP st&dy revealed that men have a higher mean n&m%er of se1&al partners at .= !hile !omen only have a /.* mean n&m%er of se1&al partners. ogether they have a mean of *. se1&al partners i.e. se1&al partners.
Males too engage more in samese1 se1&al e1perience at /;@ as compared to !omen !ho merely have a . @ engagement. More males also engage in commercial se1 at /=.;@ as compared to + %y females.
)ince the s&rvey covered /* months of se1&al activity %y the respondents, the n&m%er of !ee's in a /*month period !as divided %y the n&m%er of se1&al partners. he res<ing ?g&re constit&te the average commitment period of the respondents or the n&m%er of !ee's the se1&al activity !o&ld last.
'.&. Protection
In the same st&dy made %y UP, a s&rvey on &se of condoms among call center agents d&ring their last cas&al se1 !as also cond&cted.
call center agents,
involving ; males and /+ females responded to the G&estions.
Based on the UP st&dy, the follo!ing ass&mption can %e made7
Male call center agents since they engage more in se1&al activity have a slightly higher condom &se !ith 9/.;@ of the male respondents admitting they have engaged in protected se1. 9+@ of the female respondents said they too, engage in the practice. ogether they constit&te 9/.@ of the total n&m%er of respondents !ho engage in safe se1.
'.' Aids !est
In the same st&dy, a s&rvey of *E call center agents, involving *+ males and E females on !hether they have ta'en an AID) test !as cond&cted.
Based on the UP st&dy, the follo!ing ass&mptions can %e made7
+@ of the male respondents said they had &ndergone an AID) test. ogether they constit&te 9/.@ of the total n&m%er of respondents !ho engage in safe se1.
'. M#$+, SP+CI-ICA!I# his st&dy &ses an agent%ased sim&lation soft!are called et #ogo ;.*./ 2*++;3 principally a&thored %y Uri (ilens'y. Using high ris' lifestyle i.e. m<iple partners and &nprotected se1 as the parameters mitigated only %y condom &se and AID) test, the soft!are sim&lates the spread of "IV vir&s. Based on the aforementioned parameters the soft!are provides sliders for the follo!ing7
IIIA#P0P#7 "o! many people sim&lation %egins !ith. AV
7 Feneral li'elihood mem%er of pop&lation has se1 AV7 Average freG&ency mem%er of pop&lation !ill chec' their "IV stat&s in a /year time period.
he redcolored agents in the sim&lation are those infected !ith "IV: the green colored, those !ho are not infected and the %l&e agents are those !ho may or may not have the vir&s.
. M#$+, VA,I$A!I# A$ S+SI!IVI!/ AA,/SIS Based on the ass&mptions and data mentioned in the previo&s chapter, a sim&lation model !as generated &sing agent%ased sim&lation programming lang&age #0F0 2*++;3.
)ince the st&dy !as made in *++E,
an
//year
st&dy
involving
2representing
sim&lation
/9 the
people average
n&m%er of respondents !ho replied in the UP st&dy3 !as cond&cted in order to ma'e the *+*+
predictive
sim&lation
model.
.(. Male and fe0ale se)ual behavior
he ?rst sim&lation model in this st&dy &ses an average co&pling tendency of *. %ased on the act&al data gathered %y the UP Pop&lation Instit&te on the respondents- n&m%er of se1&al partners the past /* months prior to the s&rvey. he *+ !ee's average commitment is derived %y dividing the n&m%er of !ee's in a year %y the average co&pling tendency. Fiven these parameters, the res< is com%ined rate of ;.;E@ among male and female call center agents. his is m&ch lo!er compared to the = percent infection rate reported %y D0" as of J&ne *+/;. he discrepancy co&ld %e d&e to the fact that the D0" s&rvey does not incl&de only call center agents.
"o!ever, considering it is a predictive model for the ne1t ?ve years 2from *+/;3 &sing *++E data, it is still a very conservative estimate. 4actor in&encing the sim&lation is the less ris'y se1&al %ehavior of female call center agents that is a5ecting the overall res<.
.&. More ris1y behavior by 0en
$hanging the varia%les %y foc&sing on the data on male se1&al practices alters the res< dramatically.
Using data involving males only res<s in higher percentage of infection. $hanging the average co&pling tendency to .= 2the mean n&m%er of m<iple partners %y male call center agents according to the UP st&dy3 and r&nning the sim&lation in et #ogo: %y *+*+, male call center agents !ill have a E.+E@ rate of infection. his is higher than the com%ined infection rate of ;.;E@ involving male and female call center agents.
he res< apparently is mitigated %y the average test freG&ency of .+ times per year and a /.; average condom &se per statistics from the UP Pop&lation Instit&te st&dy.
he res< is consistent !ith the D0" report stating that male to male se1 is second highest ca&se of the spread of the "IV vir&s in $e%& $ity.
.'. More e)posure 0eans 0ore chances of infection
4rom /9 initial people, the ?g&re is raised to **+ to incl&de ;+@ of the remaining see !hat !o&ld %e the res< !ith more people involved. )im&lating the spread of the vir&s %y *+*+ !ith the ne! data, res<s in an even higher rate of infection at /C.@.
Increasing the initial people in the model also increases the percent of infection. It means the greater the e1pos&re of a pro%a%le "IV positive call center agent,
the
greater
are
the
chances of him infecting other people.
..
More
se)ual
partners
0eans an e)ponential rise of infection
Increasing the n&m%er of se1&al partners %y merely ro&nding o5 the .= mean n&m%er of se1&al partners to 9 res<s in an e1ponential increase in the percentage of infection. (ith the change in the data and r&nning a sim&lation in et #ogo, %y *+*+ an alarming @ rate of infection is estimated.
he sim&lation sho!s more and more people infected. As sho!n %y the sim&lation, %y the end of ;=* !ee's, the infection still has not sta%ilized. 2. C#C,%SI#
Based on the data from UP and the sim&lation made !ith et #ogo, male call center agents in $e%& !ith their high ris' se1&al %ehavior have more chances of getting infected %y the "IV vir&s. his ?nding is consistent !ith the ?ndings of D0"
he spread of the "IVLAID) is %ecoming to %e the &nderside of $e%& $ity-s rapid development. (ith an economy propelled mainly %y 04( remittances and the BP0 Ind&stry, the spread of the vir&s, li'e in other cities aro&nd the !orld, seem to tag along !ith the city-s development. Phenomenon li'e this, !hich th!arts the UAID)- e5ort to end the AID) epidemic %y *++, is !hat the U %ody is trying to avoid. e! cases of cities !ith high incidence of "IV infection set %ac' glo%al e5ort to arrest the epidemic %y *++. Political leaders in $e%& $ity have to p&t the city-s AID) scenario in a glo%al conte1t to ?ght the spread of "IVLAID) !ithin and o&tside the city-s %o&ndaries.
o c&r% the spread of "IVLAID) %y inKecting dr&g &se, D0" intervened %y giving a!ay clean, &ninfected syringes to dr&g &sers. It-s a radical sol&tion !hich !as criticized heavily %y vario&s sectors incl&d ing the $h&rch. he critics sa! it as tantamo&nt to enco&raging and promoting dr&g a%&se. Aside from infecting dr&g &se, there-s also a need to c&r% "IV transmission thro&gh ris'y se1&al %ehavior, the second leading ca&se in the spread of the vir&s. (ith the BP0s- critical role in the co&ntry-s economic development, the government has to do a good %alancing act in addressing the pro%lem 2hopef&lly !ith the help of BP0 ?rms3 so as to save lives, and %efore dire conseG&ences manifest and a5ect greatly the ind&stry and the economy.
3. "+-+"+C+S
Anderson and Dahl%erg, "ighris' )e1&al Behavior in the Feneral Pop&lation 2
Joint United ations Programme on "IV and AID) 2UAID)3,
Joint United ations Programme on "IV and AID) 2UAID)3, he $ities
University of the Philippines 2UP3 Pop&lation Instit&te, #ifestyle, "ealth )tat&s and Behavior of >o&ng (or'ers in $all $enters and 0ther Ind&stries7 Metro Manila and Metro $e%&, *+/+
(ilens'y, U. 2/EE=3. et#ogo AID) model. http7LLccl.north!estern.ed&LnetlogoLmodelsLAID). $enter for $onnected #earning and $omp&terBased Modeling, orth!estern University, vanston, I#.
(ilens'y, U. 2/EEE3. et#ogo. http7LLccl.north!estern.ed&LnetlogoL. $enter for $onnected #earning and $omp&terBased Modeling, orth!estern University, vanston, I#
(.( AI$S and Cities
(hile the disease seems to spread discreetly among individ&als, the rise of "IV and AID) infection a5ect cities considera%ly considering the follo!ing statistics from the UAID)- he $ities
