Background: Despite the availability of sound TB control strategies, TB remains a major health problem in developing countries including Ethiopia. A quarter of the global TB burden is from Africa. TB is among the top 10 health issues in Ethiopia. Amhara Region is one of the high TB burden regions in Ethiopia with varying magnitude across its zones and woredas. East Gojjam Zone of the Amhara Region is reported for its high TB burden with the least TB case detection performance from all zones in the region. Thus, assessing the magnitude and distribution of PTB, and exploring barriers hindering the performance of TB case detection is important in the zone. Objectives: This study aimed at assessing the spatial-temporal clustering of pulmonary TB cases, the magnitude of TB infectious period, potential barriers of TB case detection, and accessibility to and readiness of health facilities for TB services in the East Gojjam Zone, Northwest Ethiopia. Methods: This study used cross-sectional, longitudinal and qualitative study designs. Structured questionnaires, in-depth interviews and focus group discussion guides, data extraction guideline, and tape recorder were data collection tools. All pulmonary TB cases during 2013 -2019, geographic coordinates, and study area population were data inputs of spatial-temporal analysis. For the TB infectious period and barriers of TB case detection, 30% of 120 health facilities were randomly selected as study sites. All adult pulmonary TB patients taking their anti-TB treatment in those selected health facilities were interviewed and followed to determine the magnitude of TB infectious period. Twenty-seven in-depth interviews (21 among pulmonary TB patients and six among TB control program officers) and six focus group discussions involving 40 health workers were conducted for qualitative data. For geographic accessibility to and TB service readiness, all health facilities were assessed using a facility assessment tool adapted from the national and WHO standard checklists. Quality of data was assured by training of data collectors, questionnaire pretesting, using data collection guideline, regular supervision, checking data completeness, double data entry, checking for model fitness, audit trial, using thick descriptions, peer-reviewing, and using triangulated data collection method and sources. Various descriptive statistics such as mean, median, interquartile range (IQR), percent, proportions, and rates were computed using SPSS version 25. Multivariable logistic regression and negative binomial regression analyses were used to identify factors of TB infectious period and TB incidence rate, respectively. ArcGIS 10.6 was applied to conduct spatial autocorrelation analysis and map statistically significant clusters of pulmonary TB cases. Kulldorff’s scan statistics were computed to detect spatial-temporal clustering of pulmonary TB cases at the kebele level (lowest administration unit) using SatScan TM v 9.6. In all the statistical tests, necessary assumptions were checked and significance was judged at p < 0.05. In addition, qualitative data were transcribed, coded, grouped into themes, and analyzed thematically using NVivo 12 software. Results: A total of 5340(52%) smear-positive and 4928 (48%) smear-negative pulmonary TB cases were included in the analysis. Over half, 5,751(56%) cases were males and 5,545 (54%) of them were from rural areas. The overall annual case notification rates of PTB cases at zone, woreda and kebele levels were 58 (range: 47-69), 82 (range: 56-204), and 69(range: 36-347) per 100,000 population, respectively. The purely spatial cluster analysis identified eight most likely clusters (one for overall and one per year for seven years) and 47 secondary clusters. Similarly, the space-time scan analysis identified one most likely and seven secondary clusters. The purely temporal analysis also detected one most likely cluster from 2013 -2015. The magnitude of the TB infectious pool in the study area was 78,031 infectious person-days. The undiagnosed TB cases (44,895 days), smear-positive (14,625 days) and smear-negative (12,995 days) were major contributors to the infectious pool. Residence, knowledge, form of TB, smoking, alcoholism, distance from the facility, comorbidities, and stigma were statistically significant factors of the TB infectious period. This study explored several barriers hindering TB case detection that were grouped into three major themes and 14 sub-themes: 1) patient-related barriers including rural residence, low income, poor health literacy and health-seeking delay; 2) healthcare system barriers grouped into two sub- themes: health workers barriers (shortage of health workers, lack of training access, and low level on knowledge and skills), and health facility barriers (health service delay, using only passive TB case detection, poor health education provision, and lack of regular supervision and timely feedback); 3) socio-cultural and environmental barriers including stigma and discrimination, absence of health information sources, poor transportation facilities and community resistance. The overall TB service coverage was 23% (range:10 -85%). The mean distance from the nearest health facility was 8km (range: 0.5-16km). About 32% of kebeles had poor accessibility to TB services. Although 114(95%) health facilities offered at least one TB service, 44(38.6%) of them had no sputum smear microscopy. The overall TB service readiness was 63.5%: first-line anti-TB drugs (97%), diagnostics (63%), trained staff, diagnostic and treatment guidelines (53%) and laboratory supplies (41%). Lack of staff, limited commodity suppliers, inadequate budget, poor management, and geographic locations were barriers to TB service readiness. Conclusions and recommendations: The distribution of pulmonary TB cases was clustered and most of the clusters were detected in the central, northern and northwest parts of the zone. The study reported a high magnitude of TB infectious period. The physical accessibility and readiness of health facilities were poor and worse in rural and border areas. Residence, knowledge of TB, personal behaviors, comorbidities, and stigma were factors of the TB infectious period. Barriers related to patients, environmental, socio-cultural, health facilities, geographic inaccessibility and shortage of (budget, suppliers, staff) had confronted TB service readiness and TB case detection. Promoting community health literacy, scale-up of access and quality of TB diagnostics, complementing passive TB case detection with active TB case detection approach, conducting regular supervision and timely feedback, enhancing the capacity of suppliers, arranging regular refresher training and staff motivation schemes, good management practice, and engaging local political leaders to address budget and transportation problems are crucial to enhance the performance of TB control program. Keywords: TB, spatial-temporal clustering, TB infectious period, TB case detection, factors, TB service readiness, barriers, East Gojjam zone, Ethiopia.