A 10 year study of the cause of death in children under 15 years in Manhiça, Mozambique

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Study Justification:
– The study aims to address the lack of documentation on causes of mortality in Sub-Saharan Africa, specifically in Manhiça, Mozambique.
– The study provides valuable information on the most frequent causes of death in children under 15 years of age in the study area.
– The results highlight the challenges in combating infectious diseases in the region.
Study Highlights:
– The study was conducted between 1997 and 2006 in the Manhiça Health Research Centre.
– Verbal autopsy interviews were conducted on 80.4% of the recorded deaths in children under 15 years of age.
– Communicable diseases accounted for 73.6% of the causes of death, followed by non-communicable diseases (9.5%) and injuries (3.9%).
– Malaria was the leading cause of death, accounting for 21.8% of cases, followed by pneumonia (9.8%), HIV/AIDS (8.3%), and diarrhoeal diseases (8%).
Recommendations:
– The study highlights the need for targeted interventions to address infectious diseases, particularly malaria, pneumonia, HIV/AIDS, and diarrhoeal diseases.
– Recommendations include strengthening healthcare services, improving access to preventive measures and treatment, and implementing public health interventions to reduce the burden of these diseases.
Key Role Players:
– Ministry of Health/National Institute of Health of Mozambique
– Manhiça Health Research Centre
– Manhiça District Hospital
– Xinavane Rural Hospital
– Field workers and supervisors
– Medical doctors with experience in tropical paediatrics
Cost Items for Planning Recommendations:
– Strengthening healthcare services: funding for infrastructure improvement, equipment, and staffing
– Access to preventive measures and treatment: budget for the procurement and distribution of medications, vaccines, and insecticide-treated bed nets
– Public health interventions: funding for health education campaigns, community outreach programs, and surveillance systems
– Training and capacity building for healthcare workers and field staff
– Monitoring and evaluation of interventions: budget for data collection, analysis, and reporting

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a 10-year study using the verbal autopsy tool and the International Classification of Diseases (ICD-10) to assign causes of death. The study includes a large sample size of 3730 deaths and provides detailed information on the most frequent causes of mortality in children under 15 years in the Manhiça Health Research Centre. However, to improve the evidence, the abstract could include information on the methodology used for data collection and analysis, as well as any limitations of the study.

Background. Approximately 46 million of the estimated 60 million deaths that occur in the world each year take place in developing countries. Further, this mortality is highest in Sub-Saharan Africa, although causes of mortality in this region are not well documented. The objective of this study is to describe the most frequent causes of mortality in children under 15 years of age in the demographic surveillance area of the Manhiça Health Research Centre, between 1997 and 2006, using the verbal autopsy tool. Methods. Verbal autopsy interviews for causes of death in children began in 1997. Each questionnaire was reviewed independently by three physicians with experience in tropical paediatrics, who assigned the cause of death according to the International Classification of Diseases (ICD-10). Each medical doctor attributed a minimum of one and a maximum of 2 causes. A final diagnosis is reached when at least two physicians agreed on the cause of death. Results. From January 1997 to December 2006, 568499 person-year at risk (pyrs) and 10037 deaths were recorded in the Manhiça DSS. 3730 deaths with 246658 pyrs were recorded for children under 15 years of age. Verbal autopsy interviews were conducted on 3002 (80.4%) of these deaths. 73.6% of deaths were attributed to communicable diseases, non-communicable diseases accounted for 9.5% of the defined causes of death, and injuries for 3.9% of causes of deaths. Malaria was the single largest cause, accounting for 21.8% of cases. Pneumonia with 9.8% was the second leading cause of death, followed by HIV/AIDS (8.3%) and diarrhoeal diseases with 8%. Conclusion. The results of this study stand out the big challenges that lie ahead in the fight against infectious diseases in the study area. The pattern of childhood mortality in Manhiça area is typical of developing countries where malaria, pneumonia and HIV/AIDS are important causes of death.

Manhiça district is located in southern Mozambique, in the Maputo Province, about 80 km north of Maputo City. The area has two distinct regions. The first is the fertile lowlands, comprising the Incomati River flood plain running from the northern to the southern district boundary. This area is poorly inhabited and used mainly for sugarcane and fruit plantations. The second area is an escarpment of moderate altitude bordering the west of the river, where the population inhabits an extensive plateau. There are two distinct seasons, a warm and rainy season between November and April and dry and cool season during rest of the year. A full description of the geographical and sociodemographic characteristics of the study area has been presented elsewhere [7,8]. The Manhiça Demographic Surveillance System (DSS) in Manhiça District was established in 1996, and currently covers a 500 square kilometre area. An initial census was carried out in 1996, and vital events registration (births, deaths, pregnancy and, in/out-migration) were conducted on quarterly basis until the year 2000, when this was changed to twice yearly. Verbal Autopsies (VA) data collection started in 1997 with the aim of generating cause-specific mortality data in the study area. Initially, VA were conducted only in January and July on deaths of children aged less than 15 years reported through the DSS in the previous 6 months. Since the introduction of new questionnaires in June 2002 through the MTIMBA (Malaria Transmission Intensity and Mortality Burden Across Africa) project from INDEPTH, VA interviews are carried out every day by a well-trained lay supervisor and field workers. There are two referral health facilities in Manhiça district, the Manhiça District Hospital (MDH), with 110 beds, and the Xinavane Rural Hospital (XRH), with 59 beds. In addition, 10 peripheral health facilities complete the official health facilities network. Most of the government medical services are provided free of charge except for drugs prescribed at the outpatient department that is available for purchase at subsidized prices. Adults pay a symbolic consultation fee of about USD 0.02. Since 1996 the Manhiça Health Research Center (CISM) has been operating a round-the-clock, hospital-based morbidity surveillance system for children under 15 years of age attending the MDH and three other peripheral health facilities in the study area [8]. Voluntary counselling and testing to prevent mother to child transmission with Niverapina since 2003, and Highly Active Anti Retroviral Therapy (HAART) are available since 2004 for all patients including pregnant women in MDH, according to national policies. Obstetric services including obstetric emergency care, operation room and morbidity surveillance system were established at the MDH maternity clinic, as a passive case detection system, for all women (pregnant, puerperal and women with gynaecological complaints) attending this clinic with clinical complaints (i.e., not for those attending the routine antenatal clinic). Between 1997 and 2005, the number of inhabitants living in the study area increased from 32856 to 79783, due to population growth and the extension of the DSS area in August 2002. During these years, the total fertility rate decreased from 5.2 to 4.8 children per woman. The infant mortality risk in 2005 was 77.5 per 1000 live births, the under five mortality (5q0) rate was 138.6 deaths per 1000 pyrs, and the life expectancy at birth was 40.2 years [9]. The methodology used in identifying vital events in the study area has been fully described elsewhere [7]. Information on deaths comes from one of several sources: (I) household visits twice a year that are conducted to record all deaths and other demographic events that have occurred since the previous visit, (II) daily visits to hospital wards and maternity clinics by supervisors to gather information on all deaths and pregnancy related events that have taken place in the previous 24 hours and (III) weekly reports by local key informants on births, deaths and migrations that might be missed during household census visits by field workers and supervisors. Age is ascertained by direct questioning, referral to any existing personal identification documents and, if necessary, an area-specific calendar of events is used. An identification card is issued to all children under 15 years of age to allow identification of patients in the morbidity surveillance system in the MDH. Initially, eight medical students conducted VA interviews in the study area twice a year. The work was supplemented after June 2002 by a lay supervisor and field workers who interviewed key community informants and relatives of the deceased, daily. Between three and six months after a death, a field worker visited the family of the deceased to inquire whether they would accept to participate in a verbal autopsy. Upon acceptance, an oral consent was obtained from the interviewee and a date for the interview was agreed. On the day of the interview, a signed or fingerprinted informed consent (IC) was sought before the VA took place. To ensure consent within the family, potential interviewers were given an information sheet with study objectives and procedures during the initial contact, and were encouraged to discuss with family members before proceeding. Interviewers who could not read were free to ask their relatives to read the document for them. The primary informant was, whenever possible, the person who directly took care of the deceased child during the illness or condition that led to death. If the primary respondent was absent, information was sought from any other adult, including neighbours, who might have relevant information on the possible cause of death. In order to maintain confidentiality, only the coding physicians and the data entry clerks had access to the assigned causes of death. A demographer was in charge of controlling the data quality through an on-site review of questionnaires. After fieldwork, all questionnaires were checked for consistency and completeness. Questionnaires needing corrections were returned to the field within two weeks of their receipt. The study used a VA questionnaire standardized from INDEPTH [7] and adapted from the WHO model [10]. The standard questionnaire in Manhiça was written in Portuguese. However, the fieldworkers perform an on-site translation of the questions into the local language (Xangana). The questionnaire included questions on the identification of the deceased and the respondent as well as the health seeking behaviour and use of health services by the deceased prior to the death. The questionnaire also had an open-ended section where circumstances surrounding the death of the child, as well as the signs and symptoms presented during the illness preceding death, are recorded. The final section had closed questions on signs and symptoms preceding the death that did not focus on any particular disease. To assign the cause(s) of death, diagnoses are given using a standardised coding system. Three physicians with experience in tropical diseases independently assigned the cause of death using the International Classification of Diseases (ICD-10) [11]. Each physician ascribes a minimum of one and a maximum of 2 causes. Conditions should be additive and not alternative. For example, if more than one diagnosis was mentioned, it may be classified as “malaria or pneumonia,” but should be stated as “malaria and pneumonia”. A final diagnosis was reached when at least two physicians agree on the cause of death. When at least two physicians assigned “unknown” as the cause of death, the final cause of death was considered undetermined. When the cause was different among the three reviewers, the final diagnosis was “not consensus”, and these deaths were not redistributed to other diagnosis groups. When two final diagnoses were assigned for the same death, each of these was individually mapped onto ICD-10 for a calculated cause-specific rate. To rank causes of death, we used the GBD tree structures [12]. The first level included three mortality groups: Group 1 consisted of deaths attributed to communicable diseases and to maternal, perinatal and nutritional conditions; Group 2 comprised deaths attributed to non-communicable diseases and, Group 3 comprised deaths due to injuries. Each of the three groups was further divided into several major subcategories (second to fourth level). Third and fourth levels were used to classify specific causes of death. Trained data entry clerks and a data manager ensured data entry into a network of computers under a Windows NT environment. Double data entry was performed by two clerks using a modified version of The Household Registration System (HRS) [13]. Inconsistencies, if any, were corrected after counter-checking with the original questionnaires. Questionnaires with errors that could not be reconciled were returned to the field for correction. The database with the VA data was linked to other DSS databases. Data management, cleaning and statistical analysis were performed using STATA (Stata Corporation 2005, Stata Statistical Software: Release 9.2 College Station, TX: StataCorp LP, USA). Time at risk of disease was calculated for each individual registered in the demographic surveillance system, subtracting periods of absence due to migration. All-cause mortality rates were calculated by dividing the number of deaths in an age group by the time at risk, and expressed as deaths per 1000 person-years at risk. We calculated cause-specific death rates for each age group by multiplying the all-cause mortality rate by the proportion of deaths assigned to each cause. The study falls within the national ethical clearance granted to the malaria epidemiological studies of the CISM (Ministry of Health/National Institute of Health of Mozambique, 1996). The participation of the respondents during the interview was voluntary and conducted only after the IC procedure described earlier. The interviews were conducted at least one month after death, when the traditional grieving period was over.

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Based on the provided information, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women and new mothers with access to important health information, such as prenatal care guidelines, nutrition advice, and postpartum care instructions. These applications can also include features like appointment reminders and emergency contact information.

2. Telemedicine: Establish telemedicine services that allow pregnant women in remote or underserved areas to consult with healthcare professionals remotely. This can help address the shortage of healthcare providers in certain regions and improve access to prenatal care and medical advice.

3. Community Health Workers: Train and deploy community health workers who can provide basic prenatal and postnatal care, as well as education on maternal health topics, in rural or hard-to-reach areas. These workers can also serve as a link between pregnant women and healthcare facilities, ensuring timely referrals and follow-up care.

4. Maternal Health Vouchers: Implement a voucher system that provides pregnant women with access to essential maternal health services, such as antenatal care visits, delivery services, and postpartum care. These vouchers can be distributed to vulnerable populations and can help reduce financial barriers to accessing quality care.

5. Transportation Support: Develop transportation initiatives that provide pregnant women with reliable and affordable transportation to healthcare facilities for prenatal visits, delivery, and postpartum care. This can help overcome geographical barriers and ensure timely access to maternal health services.

6. Maternal Health Education Campaigns: Launch targeted education campaigns to raise awareness about the importance of maternal health and the available services. These campaigns can include community workshops, radio programs, and informational materials to empower women with knowledge and encourage them to seek appropriate care.

7. Maternity Waiting Homes: Establish maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away and need to travel for delivery. These homes can provide a safe and comfortable environment for women to stay during the final weeks of pregnancy, ensuring they are close to medical care when needed.

8. Integration of Maternal Health Services: Promote the integration of maternal health services with other healthcare programs, such as family planning, HIV/AIDS prevention and treatment, and nutrition interventions. This can improve efficiency and ensure comprehensive care for women throughout the reproductive health continuum.

9. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources and expertise to expand healthcare infrastructure, enhance service delivery, and increase availability of essential supplies and medications.

10. Data-driven Decision Making: Utilize data collection and analysis tools to monitor maternal health indicators, identify gaps in service delivery, and inform evidence-based decision making. This can help prioritize interventions, allocate resources effectively, and track progress towards improving access to maternal health services.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health in Manhiça, Mozambique is to focus on addressing the causes of mortality in children under 15 years of age. This is because the study identified communicable diseases, including malaria, pneumonia, HIV/AIDS, and diarrheal diseases, as the leading causes of death in this population.

To develop this recommendation into an innovation, the following steps can be taken:

1. Strengthen healthcare infrastructure: Improve the availability and accessibility of healthcare facilities, particularly in rural areas, to ensure that pregnant women have access to quality maternal health services. This can include expanding the number of health facilities, increasing the number of skilled healthcare providers, and ensuring the availability of essential medical supplies and equipment.

2. Enhance community-based healthcare: Implement community-based healthcare programs that focus on preventive measures, early detection, and treatment of communicable diseases. This can involve training community health workers to provide basic healthcare services, educate pregnant women on disease prevention, and facilitate referrals to healthcare facilities when necessary.

3. Improve antenatal care services: Enhance antenatal care services to ensure early detection and management of potential complications during pregnancy. This can include regular check-ups, screening for infectious diseases, and providing appropriate interventions such as insecticide-treated bed nets to prevent malaria.

4. Strengthen maternal and child health education: Increase awareness and knowledge among pregnant women and their families about the importance of maternal and child health. This can be achieved through community health education programs, workshops, and the use of multimedia platforms to disseminate information on disease prevention, nutrition, and hygiene practices.

5. Enhance data collection and analysis: Continuously monitor and evaluate the impact of interventions on maternal and child health outcomes. This can be done through the establishment of a robust data collection and analysis system, which includes regular surveillance of maternal and child mortality rates, as well as the causes of death, to inform evidence-based decision-making and resource allocation.

By implementing these recommendations, it is expected that access to maternal health services will improve, leading to a reduction in maternal and child mortality rates in Manhiça, Mozambique.
AI Innovations Methodology
Based on the information provided, here are some potential recommendations for improving access to maternal health in Manhiça, Mozambique:

1. Strengthening healthcare infrastructure: Invest in improving the capacity and quality of healthcare facilities in Manhiça, including the Manhiça District Hospital and Xinavane Rural Hospital. This could involve increasing the number of beds, ensuring availability of essential medical equipment and supplies, and improving the skills and training of healthcare providers.

2. Enhancing community-based healthcare services: Implement community-based healthcare programs to bring essential maternal health services closer to the population. This could involve training and deploying community health workers who can provide basic antenatal care, postnatal care, and health education to pregnant women and new mothers in their communities.

3. Increasing access to family planning services: Promote and provide access to family planning services to help women and couples make informed decisions about their reproductive health. This could involve expanding the availability of contraceptives, providing counseling on family planning methods, and addressing cultural and social barriers to contraceptive use.

4. Improving transportation and referral systems: Address transportation challenges by improving road infrastructure and ensuring reliable transportation options for pregnant women in need of emergency obstetric care. Additionally, establish effective referral systems between community health centers and higher-level healthcare facilities to ensure timely access to specialized care when needed.

5. Strengthening health information systems: Enhance the collection, analysis, and use of health data to inform decision-making and monitor progress in maternal health. This could involve implementing electronic health records systems, conducting regular data audits, and using data for evidence-based planning and resource allocation.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed using the following steps:

1. Baseline data collection: Gather data on the current state of maternal health in Manhiça, including indicators such as maternal mortality rate, antenatal care coverage, skilled birth attendance, and access to emergency obstetric care.

2. Define simulation parameters: Determine the specific variables and assumptions to be used in the simulation model. This could include factors such as population size, healthcare infrastructure capacity, utilization rates, and expected changes in behavior or service provision.

3. Model development: Develop a simulation model that incorporates the recommended interventions and their potential impact on maternal health outcomes. This could involve using mathematical equations, statistical models, or computer simulations to project changes in key indicators over time.

4. Sensitivity analysis: Conduct sensitivity analysis to assess the robustness of the simulation model and explore the potential range of outcomes under different scenarios or assumptions. This could involve varying input parameters and assessing the resulting changes in maternal health indicators.

5. Impact assessment: Use the simulation model to estimate the potential impact of the recommended interventions on improving access to maternal health. This could involve comparing the projected outcomes with the baseline data to quantify the expected changes in maternal mortality, antenatal care coverage, skilled birth attendance, and other relevant indicators.

6. Policy recommendations: Based on the simulation results, provide evidence-based policy recommendations for decision-makers and stakeholders. This could include identifying the most effective interventions, estimating resource requirements, and outlining a roadmap for implementation.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context and available data. The above steps provide a general framework for conducting such an analysis.

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