scholarly journals The impact of seasonal climate on new case detection rate of leprosy in Brazil (2008–2012)

2017 ◽  
Vol 88 (4) ◽  
pp. 533-542
Author(s):  
Aline Cristina Araújo Alcântara Rocha ◽  
Washington Leite Junger ◽  
Wesley Jonatar Alves Da Cruz ◽  
Eliane Ignotti
Keyword(s):  
Detection Rate ◽  
Case Detection ◽  
Case Detection Rate ◽  
Seasonal Climate ◽  
The Impact

An approach to estimating tuberculosis incidence and case detection rate from routine notification data

2015 ◽  
Vol 19 (3) ◽  
pp. 288-294 ◽  
Author(s):  
K. K. Avilov ◽  
A. A. Romanyukha ◽  
S. E. Borisov ◽  
E. M. Belilovsky ◽  
O. B. Nechaeva ◽  
...  
Keyword(s):  
Detection Rate ◽  
Case Detection ◽  
Case Detection Rate ◽  
Tuberculosis Incidence ◽  
Notification Data

scholarly journals An Evaluation of Childhood Tuberculosis Program in Chegutu District, Zimbabwe, 2020: A Descriptive Cross-Sectional Study

2021 ◽  
Author(s):  
Memory Chimsimbe ◽  
Pride Mucheto ◽  
Tsitsi Patience Juru ◽  
Addmore Chadambuka ◽  
Emmanuel Govha ◽  
...  
Keyword(s):  
Detection Rate ◽  
Cross Sectional Study ◽  
Health Facilities ◽  
Childhood Tuberculosis ◽  
Health Concern ◽  
Case Detection ◽  
Sectional Study ◽  
Cross Sectional ◽  
Case Detection Rate ◽  
Childhood Tb

Abstract Background Childhood tuberculosis (TB) is a major global public health concern contributing to significant child morbidity and mortality. A records review of the TB notification for Chegutu District Health Information System 2 (DHIS2) showed a low childhood TB case detection rate. For 2018 and 2019, childhood TB notifications were 4% and 7% respectively against the national 12% case detection rate. We evaluated the performance of the childhood TB program in Chegutu. Methods We conducted a descriptive cross-sectional study. Sixty-six health workers (HW) participated in the study. Interviewer-administered questionnaires and checklists were used to collect data on reasons for low TB case detection, HW childhood TB knowledge, program inputs, processes and outputs. Strengths, Weaknesses, Opportunities and Threats analysis was used to assess the childhood TB processes. We analyzed the data using Epi Info 7TM to generate frequencies, proportions and means. A Likert scale was used to assess health worker knowledge. Results The majority 51/66(77%) of HW were nurses and 51/66(67%) of respondents were females. Reasons for the low childhood TB case detection were lack of HW confidence in collecting gastric aspirates 55/66(83%) and HW’s negative attitudes towards gastric aspirate collection 23/66(35%). HW 24/66 (37%) had a fair childhood TB notification knowledge. The district had only one functional X-ray machine for 34 health facilities. Only 6/18 motorcycles were functional with inadequate fuel supply. No desk guide for the management of TB in children for HW (2018) was available in 34 health facilities. Ethambutol 400mg was out of stock and adult 800mg tablets were used. Funds allocated for motor vehicle and motorcycles service ($1612USD/year) were inadequate. The district failed to perform planned quarterly TB review meetings, contact tracing and childhood TB training due to funding and COVID-19 lockdown restrictions. Conclusion The childhood TB program failed to meet its targets due to inadequate inputs and suboptimal HW childhood TB knowledge. Case detection and notification can be improved through on-job training, mentorship, support and supervision and adequate resources.

scholarly journals Forecasting the new case detection rate of leprosy in four states of Brazil: A comparison of modelling approaches

Epidemics ◽  
2017 ◽  
Vol 18 ◽  
pp. 92-100 ◽  
Author(s):  
David J. Blok ◽  
Ronald E. Crump ◽  
Ram Sundaresh ◽  
Martial Ndeffo-Mbah ◽  
Alison P. Galvani ◽  
...  
Keyword(s):  
Detection Rate ◽  
Case Detection ◽  
Case Detection Rate ◽  
Modelling Approaches

scholarly journals Spatial patterns of leprosy in a hyperendemic state in Northern Brazil, 2001-2012

2015 ◽  
Vol 49 (0) ◽  
Author(s):  
Lorena Dias Monteiro ◽  
Francisco Rogerlândio Martins-Melo ◽  
Aline Lima Brito ◽  
Carlos Henrique Alencar ◽  
Jorg Heukelbach
Keyword(s):  
High Risk ◽  
Spatial Patterns ◽  
Detection Rate ◽  
Disease Risk ◽  
Late Diagnosis ◽  
Control Measures ◽  
Case Detection ◽  
Detection Rates ◽  
Case Detection Rate ◽  
Brazilian State

ABSTRACT OBJECTIVE To describe the spatial patterns of leprosy in the Brazilian state of Tocantins. METHODS This study was based on morbidity data obtained from the Sistema de Informações de Agravos de Notificação (SINAN – Brazilian Notifiable Diseases Information System), of the Ministry of Health. All new leprosy cases in individuals residing in the state of Tocantins, between 2001 and 2012, were included. In addition to the description of general disease indicators, a descriptive spatial analysis, empirical Bayesian analysis and spatial dependence analysis were performed by means of global and local Moran’s indexes. RESULTS A total of 14,542 new cases were recorded during the period under study. Based on the annual case detection rate, 77.0% of the municipalities were classified as hyperendemic (> 40 cases/100,000 inhabitants). Regarding the annual case detection rate in < 15 years-olds, 65.4% of the municipalities were hyperendemic (10.0 to 19.9 cases/100,000 inhabitants); 26.6% had a detection rate of grade 2 disability cases between 5.0 and 9.9 cases/100,000 inhabitants. There was a geographical overlap of clusters of municipalities with high detection rates in hyperendemic areas. Clusters with high disease risk (global Moran’s index: 0.51; p < 0.001), ongoing transmission (0.47; p < 0.001) and late diagnosis (0.44; p < 0.001) were identified mainly in the central-north and southwestern regions of Tocantins. CONCLUSIONS We identified high-risk clusters for transmission and late diagnosis of leprosy in the Brazilian state of Tocantins. Surveillance and control measures should be prioritized in these high-risk municipalities.

scholarly journals Weak Intra-facility Referral Linkages: Missed Opportunity for Tuberculosis Case Detection and Treatment in a Tertiary Health Facility in Benue State, Nigeria

2020 ◽  
Vol 3 (4) ◽  
pp. 444-449
Author(s):  
O Audu ◽  
OS Ogiri ◽  
S-A Igbabul ◽  
OO Ijachi ◽  
PO Enokela ◽  
...  
Keyword(s):  
Health Care Providers ◽  
Low Income ◽  
Detection Rate ◽  
Statistical Significance ◽  
Scale Up ◽  
Case Detection ◽  
Care Providers ◽  
Tuberculosis Case ◽  
Female Ratio ◽  
Case Detection Rate

Despite the scale up of quality-assured Tuberculosis diagnostic and treatment strategies over the years, case detection rate remains a serious challenge globally and particularly in Nigeria. Integrated service delivery is essential to addressing some of the challenges, but it's often neglected especially in low income settings. Recognizing these limitations, a 27-months retrospective review of all presumptive Pulmonary Tuberculosis cases sent to the directly observed short course treatment centre of Benue State University Teaching Hospital, a tertiary health institution in north central Nigeria was conducted to assess the source of referrals and diagnostic processes including outcome of the tests. Chi- square (χ2) test was used for test of association between the intra-facility linkages/referrals system and the tuberculosis case detection rate, with statistical significance set at p-value of ≤5%. There were 918 presumptive Tuberculosis cases with male to female ratio (M: F) of 1:1.3. The mean age of patients was 41.0.0 ±18.4 years. Majority (33.7%, n=) of the referrals were from general outpatient department of the hospital, followed by sexually transmitted infection clinic (26.0%) and Paediatrics department (1.6%, n=). The diagnostic positive rate was 145(15.8%). Overall, 295(32.2%) did not collect their results, of these 76(25.8%) were positive and 219(74.2%) were negative. The relationship between the missed cases and the weak intra-facility referral linkages was statistically significant (p=0.000). The hospital management should consider the engagement of all relevant health care providers on efficient two-way referral system towards ensuring adequate Tuberculosis case notification and prompt treatment.

scholarly journals Impact of organizational climate and job involvement on leprosy surveillance performance in Sampang District, Indonesia

2019 ◽  
Author(s):  
Hafid Wabula ◽  
Thinni Nurul Rochmah ◽  
Djazuly Chalidyanto ◽  
Hanin Dhany Robby
Keyword(s):  
Organizational Climate ◽  
Random Sampling ◽  
Detection Rate ◽  
Job Involvement ◽  
Case Detection ◽  
Treatment Facility ◽  
Cross Sectional ◽  
Case Detection Rate ◽  
Primary Health ◽  
Cross Sectional Design

Leprosy prevalence in Sampang District, one of the high endemic areas of leprosy in East Java Province, was detected to have higher case detection rate (51.0/100,000 people) than the target (<20/100,000). The present study aims to analyze the influence of job involvement and organizational climate on surveillance performance of leprosy in the Primary Healthcare of Sampang District. The research is observational analytic with a cross-sectional design. This study involved 21 teams of controlling and prevention of Leprosy from primary health care in Sampang District from April-June 2016. The sample was taken by proportional stratified random sampling which was divided into the treatment facility and non-treatment facility. The statistical analysis used regression linear test. The result showed a good category on organizational climate and high category of job involvement. Both organizational climate and job involvement significantly influenced the increase of staffs’ performance in leprosy surveillance. It is concluded that case detection rate of leprosy in Sampang could achieve the target when the team has a supportive organizational climate and job involvement.

The Role of Social Capital and Community Participation in Case Detection Rate (CDR) of Tuberculosis: A Case Study of Sukoharjo District, Indonesia

2017 ◽  
Vol 23 (4) ◽  
pp. 3486-3489
Author(s):  
Endang Sutisna Sulaeman ◽  
. Reviono ◽  
Rifai Hartanto ◽  
Bhisma Murti ◽  
Mohammad Fanani
Keyword(s):  
Social Capital ◽  
Community Participation ◽  
Detection Rate ◽  
Case Detection ◽  
Case Detection Rate
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