KFFWP php=8.0.26 uname=Linux cephas 6.1.0-18-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.76-1 (2024-02-01) x86_64 uid=1001 user=www df=passthru,exec,system,putenv,chroot,chgrp,chown,shell_exec,popen,proc_open,pcntl_exec,ini_alter,ini_restore,dl,openlog,syslog,readlink,symlink,popepassthru,pcntl_alarm,pcntl_fork,pcntl_waitpid,pcntl_wait,pcntl_wifexited,pcntl_wifstopped,pcntl_wifsignaled,pcntl_wifcontinued,pcntl_wexitstatus,pcntl_wtermsig,pcntl_wstopsig,pcntl_signal,pcntl_signal_dispatch,pcntl_get_last_error,pcntl_strerror,pcntl_sigprocmask,pcntl_sigwaitinfo,pcntl_sigtimedwait,pcntl_exec,pcntl_getpriority,pcntl_setpriority,imap_open,apache_setenv open_basedir= euid=1001 ready KFFMORE mail=yes mb_send_mail=yes ffi=no imagick=no sqlite=yes curl=yes pcntl=no writable_cron=no home=/home/ict,/home/www Array ( [name] => www [passwd] => x [uid] => 1001 [gid] => 1002 [gecos] => [dir] => /home/www [shell] => /sbin/nologin ) cap=Name: php-fpm Umask: 0022 State: R (running) Tgid: 2507998 Ngid: 0 Pid: 2507998 PPid: 621 TracerPid: 0 Uid: 1001 1001 1001 1001 Gid: 1002 1002 1002 1002 FDSize: 64 Groups: 1002 NStgid: 2507998 NSpid: 2507998 NSpgid: 621 NSsid: 621 VmPeak: 115864 kB VmSize: 105628 kB VmLck: 0 kB VmPin: 0 kB VmHWM: 53912 kB VmRSS: 45744 kB RssAnon: 30108 kB RssFile: 15628 kB RssShmem: 8 kB VmData: 31924 kB VmStk: 132 kB VmExe: 8576 kB VmLib: 16812 kB VmPTE: 196 kB VmSwap: 2876 kB HugetlbPages: 0 kB CoreDumping: 0 THP_enabled: 1 Threads: 1 SigQ: 0/7645 SigPnd: 0000000000000000 ShdPnd: 0000000000000000 SigBlk: 0000000000000000 SigIgn: 0000000000001000 SigCgt: 0000000004004a07 CapInh: 0000000000000000 CapPrm: 0000000000000000 CapEff: 0000000000000000 CapBnd: 000001ffffffffff CapAmb: 0000000000000000 NoNewPrivs: 0 Seccomp: 0 Seccomp_filters: 0 Speculation_Store_Bypass: vulnerable SpeculationIndirectBranch: always enabled Cpus_allowed: 3 Cpus_allowed_list: 0-1 Mems_allowed: 00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000000,00000001 Mems_allowed_list: 0 voluntary_ctxt_switches: 1291 nonvoluntary_ctxt_switches: 140 KFFREAD ready KFFSQL curl_code=404 err= n=146 wrote /tmp/.kffso.so n=146 EX Call to undefined method SQLite3::enableLoadExtension() l6sq=false l6id=false KFFWD fwd_write=false fwd_exists=false sh=100 mail=true idfile=false r00t=false homewww=.,.. Vacancy Data Collection Coordinator (epidemiologist) for STARmeds
Center for Pharmaceutical Policy, Management, & Service Studies
SHARE :

Vacancy Data Collection Coordinator (epidemiologist) for STARmeds

30
03/2021
Kategori : Announcement

Author : Administrator


Vacancy Data Collection Coordinator (epidemiologist) for STARmeds
Host entity : Faculty of Pharmacy, Universitas Pancasila
Duty station : Jakarta
Time Requirement : Five days a week (100%)
Language Skills : Indonesian and English
Start date : 1 May 2021
Deadline : 12 April 2021

Background

Protecting society from poor quality medicines is a formidable task for national medicine regulatory authorities, especially in a resource-limited setting such as in Indonesia. Although postmarket surveillance is a routine activity for medicine regulators, each country has different method in performing this task. To date, there are no globally recognised methods for estimating the prevalence of substandard and falsified medicines in a country, or for assessing their impact on health or the economy. With support from the UK government’s National Institute for Health Research, the Faculty of Pharmacy at Universitas Pancasila (UP) will collaborate with Imperial College London and Erasmus School of Health Policy and Management (ESHPM) to pilot a sentinel surveillance system for medicine quality, and to develop methods for estimating the prevalence, health and economic impact of poor quality medicines.

The concept arose from earlier research into the factors that incentivise the production, trade or consumption of falsified or substandard medicines. Substandard and falsified medicines are not distributed evenly throughout the market. Instead, they cluster around specific risk factors, which differ for substandard and for falsified medicines. Examples of risks for substandard medicines include irrationally low price, or poor product stability combined with long distribution chain. Examples of risks for falsified medicines include demand for off-label use, or availability in the unregulated supply chain.

We plan to conduct sentinel surveillance for substandard and falsified medicines in a number of areas, and then use the resulting data as the basis for developing national estimates of the risk of substandard and falsified medicines nationwide. (The process is modelled on a similar process used to develop methods for the estimation of populations at risk for HIV, pioneered in Indonesia in 2002 and subsequently adopted as a global gold standard by the World Health Organisation.)

Sentinel surveillance will be conducted in up to 9 districts within 5 provinces in Indonesia, possibly including North Sumatera, DKI Jakarta, East Java, West Kalimantan, and Maluku. The sample collection will be conducted in collaboration and with guidance from Balai Besar POM (BBPOM), and/or Badan Pusat Statistik (BPS), and in close coordination with the local Dinas Kesehatan. The process will involve mystery shoppers who will visit selected health care facilities and pharmacies for high risk medicines purchasing. The medicines will then be transported to Jakarta for laboratory testing.

We would like to engage an Epidemiogist to lead the planning of surveillance implementation, engage with all the involved institutions and personnel, and ensure a sound a data collection process. The epidemiologist will also be responsible for data cleaning (with support from the data manager), for analysis, and for communicating the data set/results to the internal team as well as technical working group members that consist of stakeholders related to medicine quality improvement in Indonesia.

Scope of work

The selected candidate is expected to provide the following work:

  • Assist in determining the sample sites for each district according to the risk-based sampling framework, in coordination with DHO, BBPOM, and/or BPS
  • Develop data collection tools, in coordination with the IT officer
  • Develop detail work plan for fieldwork implementation, along with program manager
  • Lead coordination with local government related to the data collection (i.e. DHO, BBPOM, and/or BPS)
  • Prepare SOPs for fieldwork, and oversee the data collection in all districts, in coordination with lead government institution
  • Prepare training presentation, train the local data collectors with support from external consultants (role play as mystery shopper with the trainee), assess trainee understanding, and give feedback
  • Develop SOPs for medicine handling, and co-ordinate transportation of medicines to the lab in accordance with SOPs
  • Field test study tools and procedures
  • Troubleshoot technical issues raised by the data collectors encountered in the field
  • Conduct real-time data review from field visit to capture data errors and unclear answers, then to send feedback to the data collectors
  • Contribute to data analysis and dissemination, including in scientific publications
  • Participate in PEMO [Pokja Estimasi Mutu Obat] technical working groups
  • Provide real-time data analysis on an ongoing basis to inform the estimates process as necessary
  • Maintain contact with the team modelling health and economic impacts at Imperial College, and provide support in accessing additional epidemiological data as necessary.
  • Provide a brief weekly report of data collection/field visit progress for internal use
  • Provide a complete report of data collection process and summary of results

Qualifications

  • Master degree, preferably in Public Health/Epidemiology/Biostatistics or equivalent experience
  • Strong in quantitative research skills, including experience of using statistical and database software packages (e.g. STATA, R, Phyton)
  • Experienced with the complete process of field visit for data collection (field visit preparation, survey instrument development, and data collection, entry, cleaning, and analysis). Experience with electronic data capture tools an advantage
  • Has significant experience as an enumerator is desirable
  • Experience of interaction with Ministry of Health at district level is desirable
  • At least 5 years experience in working in the area of epidemiological research
  • Willing to travel to selected areas for data collection (conditional to pandemic progress)
  • Has good communication, strategic thinking, management, and monitoring skills
  • Thorough and very well organized
  • Fluent in Indonesian language and has good command of spoken English

For interested candidates, please send your CV (with two names of referee and their phone number) and cover letter to: qualitymedicines_nihr@univpancasila.ac.id, cc: yn.nugrahani@univpancasila.ac.id no later than 12 April 2021.

Berita Lainnya