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Introduction Surgery plays a critical role in sustainable healthcare systems. Validated metrics exist to guide implementation of surgical services, but low-income countries (LIC) struggle to report recommended metrics and this poses a critical barrier to addressing unmet need. We present a comprehensive national sample of surgical encounters from a LIC by assessing the National Health Services of Mozambique. Material and methods A prospective cohort of all surgical encounters from Mozambique’s National Health Service was gathered for all provinces between July and December 2015. Primary outcomes were timely access, provider densities for surgery, anesthesiology, and obstetrics (SAO) per 100,000 population, annualized surgical procedure volume per 100,000, and postoperative mortality (POMR). Secondary outcomes include operating room density and efficiency. Results Fifty-four hospitals had surgical capacity in 11 provinces with 47,189 surgeries. 44.9% of Mozambique’s population lives in Districts without access to surgical services. National SAO density was 1.2/100,000, ranging from 0.4/100,000 in Manica Province to 9.8/100,000 in Maputo City. Annualized national surgical case volume was 367 procedures/100,000 population, ranging from 180/100,000 in Zambezia Province to 1,897/100,000 in Maputo City. National POMR was 0.74% and ranged from 0.23% in Maputo Province to 1.78% in Niassa Province. Discussion Surgical delivery in Mozambique falls short of international targets. Subnational deficiencies and variations between provinces pose targets for quality improvement in advancing national surgical plans. This serves as a template for LICs to follow in gathering surgical metrics for the WHO and the World Bank and offers short- and long-term targets for surgery as a component of health systems strengthening.

During a disaster, comprehensive, accurate, timely, and standardized health data collection is needed to improve patient care and support effective responses. In 2017, the World Health Organization (WHO) developed the Emergency Medical Team (EMT) Minimum Data Set (MDS) as an international standard for data collection in the context of disasters and public health emergencies. The EMT MDS was formally activated for the first time in 2019 during the response to Cyclone Idai in Mozambique. The aim of this study was to analyze data collected through the EMT MDS during Cyclone Idai of 2019 and to identify the benefits of and opportunities for its future use. The EMT MDS was used for data collection. All 13 international EMTs deployed from March 27 through July 12 reported data in accordance with the EMT MDS form. The collected data were analyzed descriptively. A total of 18,468 consultations, including delivery of 94 live births, were recorded. For children under-five and those five-years and older, the top five reasons for consultation were minor injuries (4.5% and 10.8%, respectively), acute respiratory infections ([ARI] 12.6% and 4.8%, respectively), acute watery diarrhea (18.7% and 7.7%, respectively), malaria (9.2% and 6.1%, respectively), and skin diseases (5.1% and 3.1%, respectively). Non-disaster-related health events accounted for 84.7% of the total health problems recorded. Obstetric care was among the core services provided by EMTs during the response. Despite of challenges, the EMT MDS reporting system was found to support the responses and coordination of EMTs. The role of the Mozambican Ministry of Health (MOH), its cooperation with EMTs, and the dedicated technical support of international organizations enabled its successful implementation.

Background: Standardized health-data collection enables effective disaster responses and patient care. Emergency medical teams use the Japan Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) reporting template to collect patient data. EMTs submit data on treated patients to an EMT coordination cell. The World Health Organization’s (WHO) EMT minimum dataset (MDS) offers an international standard for disaster data collection. Goal: The goal of this study was to analyze age and gender distribution of medical consultations in EMT during disasters. Methods: Data collected from 2016 to 2020 using the J-SPEED/MDS tools during six disasters in Japan and Mozambique were analyzed. Linear regression with data smoothing via the moving average method was employed to identify trends in medical consultations based on age and gender. Results: 31,056 consultations were recorded: 13,958 in Japan and 17,098 in Mozambique. Women accounted for 56.3% and 55.7% of examinees in Japan and Mozambique, respectively. Children accounted for 6.8% of consultations in Japan and 28.1% in Mozambique. Elders accounted for 1.32 and 1.52 times more consultations than adults in Japan and Mozambique, respectively. Conclusions: Study findings highlight the importance of considering age-specific healthcare requirements in disaster planning. Real-time data collection tools such as J-SPEED and MDS, which generate both daily reports and raw data for in-depth analysis, facilitate the validation of equitable access to healthcare services, emphasize the specific needs of vulnerable groups, and enable the consideration of cultural preferences to improve healthcare provision by EMTs.

Background: African research capacity is challenged by insufficient infrastructure to solicit and manage grants from local and international funding agencies. Objective: The manuscript provides an overview and discusses lessons learned about the pioneering role of the Mozambique Institute for Health Education and Research (MIHER) as the first research support center (RSC) in supporting the management of research grants in Mozambique, emphasizing its impact on research capacity development. Methods: Using mixed methods, data were comprehensively collected to identify MIHER’s primary achievements from 2010 to 2023. The activities took place in four public universities, five training institutions for healthcare workers, and 40 public healthcare units in Mozambique. Findings: MIHER had partnership contracts with over 35 external institutions, and supported the design and implementation of one doctoral program and five masters’ degree programs at three public universities. Over 70% of the 128 MSc and three Ph.D. degree recipients have gone on to become lecturers at Mozambique’s public universities or are working in Mozambique’s public health system. Over 9,000 lecturers and healthcare workers participated in MIHER’s 261 research capacity development workshops. MIHER assisted in writing and implementing 98 research grants, amassing $29,923,197 in extramural support. Of 170 publications generated, 89% were indexed in PubMed. African researchers served as first or last author in 55% and 34% of these publications, respectively; Mozambicans were first and last authors in 44% and 23% of the articles, respectively. Two research laboratories were rehabilitated. Investments in information and communication technology also fostered training and mentorship. Conclusions: MIHER has emerged as a leading RSC of Excellence, fostering synergies and promoting a quality research culture in Mozambique, fueled in part, by its ability to identify and incorporate key collaborations. MIHER is a successful example of an RSC that can make the difference in resource‑limited settings to enable research resource mobilization, evidence-based health care delivery and policy design.

The aim of this study was to assess the surgical resources and surgical oncology team skills at the Surgical Department of Maputo Central Hospital (MCH) in Mozambique in order to define an educational program to support surgical oncology practice. From January 2017 to December 2017, a general evaluation of the resources of MCH was carried out, as well as its offerings in oncological care in different services. Data were obtained by reviewing documents, visiting surgical services and interviewing key-informants and others informally. In addition, a group of seven surgeons of the Surgical Department of MCH answered a questionnaire about the quality of the cancer units (The Cancer Units Assessment Checklist for low- or middle-income African countries). Subsequently, surgical, anaesthesiology and intensive care facilities were evaluated according to the Portuguese-speaking African Countries Assessment of Surgical Oncology Capacity Survey (PSAC-Surgery). All the data were triangulated in order to identify gaps, develop an action plan and define an educational program. Breast, oesophagus and colorectal cancers were the most commonly treated neoplasms in MCH. A range of technical and resource needs as well as the gaps in knowledge and skills were identified. All surgeons recognised the need to create a training program in oncology at the undergraduate level, specific training for residents and continuing oncological education for general surgeons to improve the practice of surgical oncology. It was evident that all these interventions needed to be formalised, appropriately certified and count for professional career progression. Based on the local epidemiological data and on these study findings, oncology education programs were developed for surgeons. The findings of this study contributed to the development of an educational program in surgical oncology, considered essential to the training of surgeons at MCH. The cancer educational programs and the mobilisation of adequate resources will ensure the provision of adequate surgical oncology treatments for MCH. The training requirements should be tailored to suit the local needs based on the most prevalent malignancies diagnosed in the region. In our view, this methodology may apply to other countries with similar realities in the formation of surgical oncologists.

Cancer is a growing concern in Mozambique. However, the country has limited facilities and few oncologists. Surgical oncologists are an unmet need. The aim of this study was to assess residents' knowledge in prevalent cancer domains and to identify and characterize prevalent cancers treated by surgery at Maputo Central Hospital, the largest hospital in Mozambique. The expectations were that the findings shall inform the development of a comprehensive curriculum in surgical oncology fellowship fit for the Hospital. To identify and characterize prevalent cancers, we performed a retrospective analysis of individual cancer patient registries of Maputo Central Hospital (MCH), Mozambique. Information was recorded into data collection sheets and analyzed with SPSS 21. To assess MCH residents oncologic knowledge, we invited Twenty-six junior residents (49% of all residents) of different specialties to take a 30 item multiple choice written test used elsewhere in previous studies. The test focused on the domains of Basis of oncology, Radiotherapy, Pathology, Chemotherapy, Pain management, Surgical oncology and Clinical Pathway. The test was administered anonymously and without prior notice. We analyzed the overall test and topic performance of residents. The study covered a period of 3 years and 203 patients. The most prevalent malignant tumors treated by general and thoracic surgery in MCH cancer registry were esophageal (7%), female breast (6.5%) and colorectal cancer (2.8%). Globally these malignancies were diagnosed at an advanced stage of the disease and required a multimodal treatment. The mean percent correct score of residents was 37.3%. The dimension with the highest percent correct score were clinical management (46%) and surgical oncology (28%) showed the lowest correct score. In Maputo, Mozambique esophageal, breast and colorectal cancer were the most prevalent malignancies treated, with surgery, by thoracic or general surgery in MCH. The test scores suggest that, among residents, the knowledge in oncology needs to be improved, rendering support to the need of a surgical oncology training tailored to suit the local needs. Specific training should take into account local cancer prevalence, resources, their quality and the support of surgical oncology services with volume and experience.

Background/Introduction:When a natural or man-made disaster occurs, emergency medical teams (EMTs) are dispatched to provide medical surge capacity for injured and sick individuals. Accurate predictions of EMTs consultations during disasters can improve dispatch and withdrawal decisions. However, no published studies have yet demonstrated a method for predicting the number of consultations or patients based on EMT activity data.Objectives:This research explores an innovative yet simple and reliable method to predict the number of consultations needed by EMTs during disasters, aiming to enhance the effectiveness and efficiency of medical response.Method/Description:Data were collected using Japan-Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) and Minimum Data Set (MDS) for five disasters in Japan and one in Mozambique. For each disaster, the number of consultations was predicted from the K value and constant attenuation model, originally developed for predicting COVID-19 patient numbers.Results/Outcomes:The total number of EMT consultations per disaster ranged from 684 to 18,468. The predicted curve and actual K data were similar for each of the disasters (R2 from 0.953 to 0.997), but offset adjustments were needed for the Kumamoto earthquake and the Mozambique cyclone because their R2 values were below 0.985. For the six disasters, the difference between the number of consultations predicted from K values and the measured cumulative number of consultations ranged from ±1.0% to ±4.1%.Conclusion:The K value and constant attenuation model reliably predicted EMT consultations during six different disasters. This simple model may be useful for the coordination of future responses of EMTs during disasters.

Background/Introduction:The WHO endorsed the Emergency Medical Team (EMT) Minimum Data Set (MDS) as a real-time data collection and reporting tool during health emergencies and disasters in 2017. It was for the first time activated in 2019 during Cyclone Idai in Mozambique. Since then, it has been used in 16 countries during various events. However, no assessment on data quality collected via MDS has been conducted.Objectives:This study aimed to assess data completeness using data from Cyclone Idai.Method/Description:We analyzed 282 daily reports containing 18,468 patient consultations from 14 international EMTs between 2019/03/27 and 2019/07/12. We considered data incomplete if inputs for demographic information, health events, outcomes, and relation to disaster were lower than the total number of patient consultations. We calculated the percentage of missing values for MDS items. Logistic regression identified associations between data incompleteness and EMT type.Results/Outcomes:Completeness of information on team and location was 100%. Incompleteness rates were 7.1% for sex and age, 37.2% for health events, 48.9% for outcomes, and 41.8% for the relation of health events to the disaster. Type 1 Fixed EMTs reported less complete data compared to Type 1 Mobile and Type 2 EMTs. Classified EMTs were more likely to report complete data.Conclusion:Overall, MDS daily report completeness needs improvement. Type 1 Fixed EMTs may have lower completeness due to busier schedules, while Type 1 Mobile EMTs benefit from more effective just-in-time training. Type 2 teams, being less busy, achieve more accurate data entry. Training for data collection is essential for better data completeness.

In 2017, the World Health Organization introduced an international standardized medical data collection tool for disasters, known as the Emergency Medical Team (EMT) Minimum Data Set (MDS). The EMT MDS was activated for the first time in 2019 in response to Cyclone Idai in Mozambique. The present study aimed to examine the daily and phase trends in acute mental health problems identified by international EMTs during their response to Cyclone Idai and reported using the EMT MDS. Joinpoint regression analysis was used to examine daily trends in acute mental health consultations. Trends were also examined by phases, which were identified using joinpoints. During the 90-day EMT response period following Cyclone Idai, 94 acute mental health consultations were reported. The daily trend analysis showed a significant increase in the daily number and percentage of acute mental health consultations from response onset until day 13, followed by a gradual decline ( <0.05). The phase trend analysis showed a consistent decrease across the identified phases ( for trend<0.001). The findings of this study provide insight into the need for mental health support in the immediate aftermath of natural disasters and how that need may change over time.

Emerging evidence shows that inflammaging varies across populations, challenging universal immune-aging models. Urbanization in sub-Saharan Africa—characterized by reduced exposure to infectious diseases and rising rates of noncommunicable diseases—offers a natural experiment for assessing environmental effects on inflammaging. Lower inflammaging in indigenous groups may reflect adaptation to chronic infection, whereas heightened inflammation in industrialized populations suggests ecological imbalance, underscoring the need to include diverse ecological groups in aging research.