SurvNet Electronic Surveillance System for Infectious Disease Outbreaks, Germany

Krause, Gérard; Altmann, Doris; Faensen, Daniel; Porten, Klaudia; Benzler, Justus; Pfoch, Thomas; Ammon, Andrea; Kramer, Michael H.; Claus, H.

doi:10.3201/eid1310.070253

Cited by 100 publications

(80 citation statements)

References 25 publications

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“…Germany does meet these requirements as it dis- poses of an electronic case-based surveillance system since 2001 [9]. An extensive epidemiological surveillance report is published yearly [5].…”

Section: Resultsmentioning

confidence: 99%

“…Data can be continuously updated and contain demographic information about the patient, information about the disease, prior treatment, treatment outcome, and diagnostic results. Data are collected with a special software (SurvNet@rki) [9]. All analyses were performed using Excel (version 11, Microsoft Corporation, Redmond, Washington, USA) and Stata (version 12.1, StataCorp LP, Texas, USA).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Tuberculosis surveillance and control in Germany — An application of the Berlin Declaration Monitoring and Evaluation Framework

Hauer

Fiebig²,

Brodhun³

et al. 2012

European Journal of Microbiology and Immunology

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Background: In 2007, the 'Berlin Declaration on Tuberculosis' (BD) was signed by the Ministers of the WHO European Region Member States (MS) to address the re-emerging threat of tuberculosis (TB) by fully implementing the Stop TB strategy. WHO Euro developed a Monitoring and Evaluation (M&E) Framework using programmatic and epidemiological indicators to follow-up the BD from 2013 onwards. Ahead of this, we explored the Framework performance for Germany, a low TB incidence country. Methods: We selected from a surveillance perspective on five country-specific indicators asked for all MS. Information sources included guidelines, notification data and laboratory quality assurance results. Results: As to national TB guidelines (indicator 1.1.1), up-to-date guidance documents are available. Regarding external quality assurance (3.2) proficiency testing confirms high quality of culture and drug-susceptibility testing. M/XDR-TB prevention and control is reflected by a 1.7% MDR-TB rate in 2010 with decreasing tendency (4.1.2). As to treatment success (5), the WHO target of 85% is reached for all age groups except the elderly ≥60 years. Germany disposes of an electronic case-based surveillance providing evidence for TB policy and practices (5.2.2). Conclusions:The selected M&E Framework indicators proved well applicable to a low-incidence country. The results show no specific gaps in TB surveillance and control in Germany.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Tuberculosis surveillance and control in Germany — An application of the Berlin Declaration Monitoring and Evaluation Framework

Hauer

Fiebig²,

Brodhun³

et al. 2012

European Journal of Microbiology and Immunology

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“…Pelaporan pada berbagai jenjang (dari Puskesmas hingga Dirjen Pengendalian Penyakit dan Penyehatan Lingkungan serta WHO) penting dalam sistem surveilans pes sebab merupakan program nasional yang jika terjadi satu saja kasus maka berlaku peraturan karantina bagi suatu wilayah dan embargo yang berdampak pada seluruh bidang lain bukan hanya bidang kesehatan. Pes juga termasuk dalam International Health Regulations sehingga harus dilaporkan dari tingkat lokal sampai internasional untuk dapat mendeteksi dan mengendalikan KLB di berbagai tingkatan (Krause, et al, 2007).…”

Section: Kesederhanaanunclassified

“…Keterwakilan data surveilans bisa terhambat jika petugas di fasilitas kesehatan menutup-nutupi kasus penyakit atau dengan sengaja under reporting morbiditas epidemiologi. Hal ini karena KLB dianggap sebagai suatu kebocoran yang menunjukkan kinerja petugas yang buruk dalam pencegahan dan pengendalian penyakit di wilayahnya (Murti, 2003, Krause, et al, 2007.…”

Section: Kerepresentatifanunclassified

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Quality of Plague Surveillance System in Pasuruan Regency Year 2014 Based on Surveillance Attributes

Malikhatin

Hendrati²

2017

JBE

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ABSTRAKPenyakit pes yang merupakan penyakit zoonosa karantina masih terjadi di Kabupaten Pasuruan. Suspek kasus pes masih ditemukan sampai tahun 2013. Surveilans pes yang secara aktif dilakukan di Kabupaten Pasuruan kemungkinan merupakan satu-satunya surveilans pes yang ada di Indonesia. Surveilans pes yang dijalankan meliputi surveilans human dan rodent. Evaluasi terhadap sistem surveilans perlu dilakukan untuk meningkatkan kualitas, efisiensi,dan kemanfaatan sistem surveilans itu sendiri. Tujuan penelitian ini adalah untuk menilai kualitas sistem surveilans pes tahun 2014 berdasarkan atributnya, yaitu kesederhanaan, fleksibilitas, akseptabilitas, kualitas data, sensitifitas, nilai prediktif positif, kerepresentatifan, ketepatan waktu,dan stabilitas. Desain penelitian ini adalah studi evaluasi. Subyek adalah sistem surveilans pes di Kabupaten Pasuruan sepanjang tahun 2014. Pengumpulan data dilakukan dengan teknik wawancara, observasi,dan telaah dokumen. Data dan informasi yang diperoleh dibandingkan dengan pedoman dan teori yang ada kemudian disajikan dalam bentuk narasi, tabel,dan gambar. Hasil menunjukkan bahwa sistem surveilans yang ada sudah sederhana dan fleksibel, kualitas data dan aksepatabilitas rendah, sensitifitas dan NPP tidak dapat diukur, kerepresentatifan dan ketepatan waktu rendah, serta stabilitas tinggi. Kesimpulan yang dapat ditarik adalah kualitas sistem surveilans pes di Kabupaten Pasuruan berdasarkan atributnya masih belum baik. Saran untuk pelaksanaan surveilans pes adalah melakukan pelatihan, menyediaan dana yang cukup, monitoring dan evaluasi secara berkala, melakukan diseminasi informasi kepada lintas sektor, lintas program,dan masyarakat, mengirimkan laporan surveilans melalui e-mail, menggunakan software spreadsheet untuk laporan surveilans rodent, menyempurnakan laporan dengan memasukkan keterangan tentang serum yang rusak, serum kurang sesuai jumlah tangkapan rodent,dan trap yang hilang.

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Bayesian outbreak detection in the presence of reporting delays

et al. 2015

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One use of infectious disease surveillance systems is the statistical aberration detection performed on time series of counts resulting from the aggregation of individual case reports. However, inherent reporting delays in such surveillance systems make the considered time series incomplete, which can be an impediment to the timely detection and thus to the containment of emerging outbreaks. In this work, we synthesize the outbreak detection algorithms of Noufaily et al. (2013) and Manitz and Höhle (2013) while additionally addressing right truncation caused by reporting delays. We do so by considering the resulting time series as an incomplete two-way contingency table which we model using negative binomial regression. Our approach is defined in a Bayesian setting allowing a direct inclusion of all sources of uncertainty in the derivation of whether an observed case count is to be considered an aberration. The proposed algorithm is evaluated both on simulated data and on the time series of Salmonella Newport cases in Germany in 2011. Altogether, our method aims at allowing timely aberration detection in the presence of reporting delays and hence underlines the need for statistical modeling to address complications of reporting systems. An implementation of the proposed method is made available in the R package surveillance as the function "bodaDelay".

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SurvNet Electronic Surveillance System for Infectious Disease Outbreaks, Germany

Abstract: Electronic Surveillance System for Infectious Disease Outbreaks, GermanyThis system has managed detailed information on 30,578 disease outbreaks.

Cited by 100 publications

References 25 publications

Tuberculosis surveillance and control in Germany — An application of the Berlin Declaration Monitoring and Evaluation Framework

Tuberculosis surveillance and control in Germany — An application of the Berlin Declaration Monitoring and Evaluation Framework

Quality of Plague Surveillance System in Pasuruan Regency Year 2014 Based on Surveillance Attributes

Bayesian outbreak detection in the presence of reporting delays

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