RESUMEN

INTRODUCTION: In 2018, the Mozambique Ministry of Health launched guidelines for implementing differentiated service delivery models (DSDMs) to optimize HIV service delivery, improve retention in care, and ultimately reduce HIV-associated mortality. The models were fast-track, 3-month antiretrovirals dispensing, community antiretroviral therapy groups, adherence clubs, family approach and three one-stop shop models: adolescent-friendly health services, maternal and child health, and tuberculosis. We conducted a cost-effectiveness analysis and budget impact analysis to compare these models to conventional services. METHODS: We constructed a decision tree model based on the percentage of enrolment in each model and the probability of the outcome (12-month retention in treatment) for each year of the study period-three for the cost-effectiveness analysis (2019-2021) and three for the budget impact analysis (2022-2024). Costs for these analyses were primarily estimated per client-year from the health system perspective. A secondary cost-effectiveness analysis was conducted from the societal perspective. Budget impact analysis costs included antiretrovirals, laboratory tests and service provision interactions. Cost-effectiveness analysis additionally included start-up, training and clients' opportunity costs. Effectiveness was estimated using an uncontrolled interrupted time series analysis comparing the outcome before and after the implementation of the differentiated models. A one-way sensitivity analysis was conducted to identify drivers of uncertainty. RESULTS: After implementation of the DSDMs, there was a mean increase of 14.9 percentage points (95% CI: 12.2, 17.8) in 12-month retention, from 47.6% (95% CI, 44.9-50.2) to 62.5% (95% CI, 60.9-64.1). The mean cost difference comparing DSDMs and conventional care was US$ -6 million (173,391,277 vs. 179,461,668) and -32.5 million (394,705,618 vs. 433,232,289) from the health system and the societal perspective, respectively. Therefore, DSDMs dominated conventional care. Results were most sensitive to conventional care interaction costs in the one-way sensitivity analysis. For a population of 1.5 million, the base-case 3-year financial costs associated with the DSDMs was US$550 million, compared with US$564 million for conventional care. CONCLUSIONS: DSDMs were less expensive and more effective in retaining clients 12 months after antiretroviral therapy initiation and were estimated to save approximately US$14 million for the health system from 2022 to 2024.

Asunto(s)

RESUMEN

Emerging zoonotic diseases are an increasing threat to public health. There is little data on the seroprevalence of zoonotic diseases among pastoralists in the country. We aim to carry out a cross-sectional study on the prevalence of major zoonotic diseases among pastoral communities in the Caia and Búzi districts. Methods: Between January and December 2018, a questionnaire was used to solicit socio-demographic data from consenting pastoralists with the collection of blood samples in the Caia and Búzi districts of the Sofala province. All samples were tested using ELISA commercial reagents for the detection of IgM antibodies against Brucella and Leptospira. Likewise, IgM and IgG antibodies against Rickettsia and CCHFV were determined using ELISA kits. Results: A total of 218 samples were tested, of which 43.5% (95/218) were from the district of Caia and 56.4% (123/218) from the Búzi district. Results from both districts showed that the seroprevalence of IgM antibodies against Brucella and Leptospira was 2.7% (6/218) and 30.3% (67/218), respectively. Positivity rates for IgM and IgG anti-Rickettsia and CCHFV were 8.7% (19/218), 2.7% (6/218), 4.1% (9/218), and 0.9% (2/218), respectively. Conclusions: Results from our study showed evidence of antibodies due to exposure to Brucella, Leptospira, Rickettsia, and CCHFV with antibodies against Leptospira and Rickettsia being the most prevalent. Hence, laboratory diagnosis of zoonotic diseases is essential in the early detection of outbreaks, the identification of silent transmission, and the etiology of non-febrile illness in a pastoral community. There is a need to develop public health interventions that will reduce the risk of transmission.

Asunto(s)

RESUMEN

BACKGROUND: Emerging zoonotic diseases are an increasing threat to public health. There is little data on the seroprevalence of zoonotic diseases among pastoralists in the country. We aim to carry out a cross-sectional study on the prevalence of major zoonotic diseases among pastoral communities in the Caia and Búzi districts. METHODS: Between January and December 2018, a questionnaire was used to solicit socio-demographic data from consenting pastoralists with the collection of blood samples in the Caia and Búzi districts of the Sofala province. All samples were tested using ELISA commercial reagents for the detection of IgM antibodies against Brucella and Leptospira. Likewise, IgM and IgG antibodies against Rickettsia and CCHFV were determined using ELISA kits. RESULTS: A total of 218 samples were tested, of which 43.5% (95/218) were from the district of Caia and 56.4% (123/218) from the Búzi district. Results from both districts showed that the seroprevalence of IgM antibodies against Brucella and Leptospira was 2.7% (6/218) and 30.3% (67/218), respectively. Positivity rates for IgM and IgG anti-Rickettsia and CCHFV were 8.7% (19/218), 2.7% (6/218), 4.1% (9/218), and 0.9% (2/218), respectively. CONCLUSIONS: Results from our study showed evidence of antibodies due to exposure to Brucella, Leptospira, Rickettsia, and CCHFV with antibodies against Leptospira and Rickettsia being the most prevalent. Hence, laboratory diagnosis of zoonotic diseases is essential in the early detection of outbreaks, the identification of silent transmission, and the etiology of non-febrile illness in a pastoral community. There is a need to develop public health interventions that will reduce the risk of transmission.

Asunto(s)

RESUMEN

BACKGROUND: HIV treatment has been available in Mozambique since 2004, but coverage of, and retention in, antiretroviral therapy (ART) remain suboptimal. Therefore, to increase health system efficiency and reduce HIV-associated mortality, in November, 2018, the Ministry of Health launched national guidelines on implementing eight differentiated service delivery models (DSDMs) for HIV treatment. We assessed the effect of this implementation on retention in ART 12 months after initiation, and explored the associated effects of COVID-19. METHODS: In this uncontrolled interrupted time-series analysis, data were extracted from the Mozambique ART database, which contains data on individuals in ART care from 1455 health facilities providing ART in Mozambique. We included individual-level data from facilities that were providing ART at the beginning of the study period (Jan 1, 2016) and at the start of DSDM implementation (Dec 1, 2018). We compared the proportion of individuals retained in ART 12 months after initiation between the periods before (Jan 1, 2017, to Nov 30, 2018) and after (Dec 1, 2019, to June 30, 2021) implementation of the DSDMs, overall and stratified by sex and age. We applied a generalised estimating equation model with a working independence correlation and cluster-robust standard errors to account for clustering at the facility level. In a secondary analysis, we assessed the effect of COVID-19 response measures during the post-intervention period on ART retention. FINDINGS: The study included 613 facilities and 1 131 118 individuals who started ART during the inclusion period up to June 30, 2020, of whom 79 178 (7·0%) were children (age ≤14 years), 226 224 (20·0%) were adolescents and young adults (age 15-24 years), and 825 716 (73·0%) were adults (age ≥25 years). 731 623 (64·7%) were female and 399 495 (35·3%) were male. Introduction of the DSDMs was associated with an estimated increase of 24·5 percentage points (95% CI 21·1 to 28·0) in 12-month ART retention by the end of the study period, compared with the counterfactual scenario without DSDM implementation. By age, the smallest effect was estimated in children (6·1 percentage points, 1·3 to 10·9) and the largest effect in adolescents and young adults (28·8 percentage points, 24·2 to 33·4); by sex, a larger effect was estimated in males (29·7 percentage points, 25·6 to 33·7). Our analysis showed that COVID-19 had an overall negative effect on 12-month retention in ART compared with a counterfactual scenario based on the post-intervention period without COVID-19 (-10·0 percentage points, -18·2 to -1·8). INTERPRETATION: The implementation of eight DSDMs for HIV treatment had a positive impact on 12-month retention in ART. COVID-19 negatively influenced this outcome. FUNDING: None. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.

Asunto(s)

RESUMEN

Madagascar is home to an extraordinary diversity of endemic mammals hosting several zoonotic pathogens. Although the African origin of Malagasy mammals has been addressed for a number of volant and terrestrial taxa, the origin of their hosted zoonotic pathogens is currently unknown. Using bats and Leptospira infections as a model system, we tested whether Malagasy mammal hosts acquired these infections on the island following colonization events, or alternatively brought these bacteria from continental Africa. We first described the genetic diversity of pathogenic Leptospira infecting bats from Mozambique and then tested through analyses of molecular variance (AMOVA) whether the genetic diversity of Leptospira hosted by bats from Mozambique, Madagascar and Comoros is structured by geography or by their host phylogeny. This study reveals a wide diversity of Leptospira lineages shed by bats from Mozambique. AMOVA strongly supports that the diversity of Leptospira sequences obtained from bats sampled in Mozambique, Madagascar, and Comoros is structured according to bat phylogeny. Presented data show that a number of Leptospira lineages detected in bat congeners from continental Africa and Madagascar are imbedded within monophyletic clades, strongly suggesting that bat colonists have indeed originally crossed the Mozambique Channel while infected with pathogenic Leptospira.

Asunto(s)

RESUMEN

The Countrywide Mortality Surveillance for Action platform is collecting verbal autopsy (VA) records from a nationally representative sample in Mozambique. These records are used to estimate the national and subnational cause-specific mortality fractions (CSMFs) for children (1-59 months) and neonates (1-28 days). Cross-tabulation of VA-based cause-of-death (COD) determination against that from the minimally invasive tissue sampling (MITS) from the Child Health and Mortality Prevention project revealed important misclassification errors for all the VA algorithms, which if not accounted for will lead to bias in the estimates of CSMF from VA. A recently proposed Bayesian VA-calibration method is used that accounts for this misclassification bias and produces calibrated estimates of CSMF. Both the VA-COD and the MITS-COD can be multi-cause (i.e., suggest more than one probable COD for some of the records). To fully use this probabilistic COD data, we use the multi-cause VA calibration. Two different computer-coded VA algorithms are considered-InSilicoVA and EAVA-and the final CSMF estimates are obtained using an ensemble calibration that uses data from both the algorithms. The calibrated estimates consistently offer a better fit to the data and reveal important changes in the CSMF for both children and neonates in Mozambique after accounting for VA misclassification bias.

Asunto(s)

RESUMEN

Verbal autopsies (VAs) are extensively used to determine cause of death (COD) in many low- and middle-income countries. However, COD determination from VA can be inaccurate. Computer coded verbal autopsy (CCVA) algorithms used for this task are imperfect and misclassify COD for a large proportion of deaths. If not accounted for, this misclassification leads to biased estimates of cause-specific mortality fractions (CSMFs), a critical piece in health-policy making. Recent work has demonstrated that the knowledge of the CCVA misclassification rates can be used to calibrate raw VA-based CSMF estimates to account for the misclassification bias. In this manuscript, we review the current practices and issues with raw COD predictions from CCVA algorithms and provide a complete primer on how to use the VA calibration approach with the calibratedVA software to correct for verbal autopsy misclassification bias in cause-specific mortality estimates. We use calibratedVA to obtain CSMFs for child (1-59 months) and neonatal deaths using VA data from the Countrywide Mortality Surveillance for Action project in Mozambique.

Asunto(s)

RESUMEN

Sub-Saharan Africa lacks timely, reliable, and accurate national data on mortality and causes of death (CODs). In 2018 Mozambique launched a sample registration system (Countrywide Mortality Surveillance for Action [COMSA]-Mozambique), which collects continuous birth, death, and COD data from 700 randomly selected clusters, a nationally representative population of 828,663 persons. Verbal and social autopsy interviews are conducted for COD determination. We analyzed data collected in 2019-2020 to report mortality rates and cause-specific fractions. Cause-specific results were generated using computer-coded verbal autopsy (CCVA) algorithms for deaths among those age 5 years and older. For under-five deaths, the accuracy of CCVA results was increased through calibration with data from minimally invasive tissue sampling. Neonatal and under-five mortality rates were, respectively, 23 (95% CI: 18-28) and 80 (95% CI: 69-91) deaths per 1,000 live births. Mortality rates per 1,000 were 18 (95% CI: 14-21) among age 5-14 years, 26 (95% CI: 20-31) among age 15-24 years, 258 (95% CI: 230-287) among age 25-59 years, and 531 (95% CI: 490-572) among age 60+ years. Urban areas had lower mortality rates than rural areas among children under 15 but not among adults. Deaths due to infections were substantial across all ages. Other predominant causes by age group were prematurity and intrapartum-related events among neonates; diarrhea, malaria, and lower respiratory infections among children 1-59 months; injury, malaria, and diarrhea among children 5-14 years; HIV, injury, and cancer among those age 15-59 years; and cancer and cardiovascular disease at age 60+ years. The COMSA-Mozambique platform offers a rich and unique system for mortality and COD determination and monitoring and an opportunity to build a comprehensive surveillance system.

Asunto(s)

RESUMEN

Sub-Saharan Africa lacks timely, reliable, and accurate national data on mortality and causes of death (CODs). In 2018 Mozambique launched a sample registration system (Countrywide Mortality Surveillance for Action [COMSA]-Mozambique), which collects continuous birth, death, and COD data from 700 randomly selected clusters, a nationally representative population of 828,663 persons. Verbal and social autopsy interviews are conducted for COD determination. We analyzed data collected in 2019-2020 to report mortality rates and cause-specific fractions. Cause-specific results were generated using computer-coded verbal autopsy (CCVA) algorithms for deaths among those age 5 years and older. For under-five deaths, the accuracy of CCVA results was increased through calibration with data from minimally invasive tissue sampling. Neonatal and under-five mortality rates were, respectively, 23 (95% CI: 18-28) and 80 (95% CI: 69-91) deaths per 1,000 live births. Mortality rates per 1,000 were 18 (95% CI: 14-21) among age 5-14 years, 26 (95% CI: 20-31) among age 15-24 years, 258 (95% CI: 230-287) among age 25-59 years, and 531 (95% CI: 490-572) among age 60+ years. Urban areas had lower mortality rates than rural areas among children under 15 but not among adults. Deaths due to infections were substantial across all ages. Other predominant causes by age group were prematurity and intrapartum-related events among neonates; diarrhea, malaria, and lower respiratory infections among children 1-59 months; injury, malaria, and diarrhea among children 5-14 years; HIV, injury, and cancer among those age 15-59 years; and cancer and cardiovascular disease at age 60+ years. The COMSA-Mozambique platform offers a rich and unique system for mortality and COD determination and monitoring and an opportunity to build a comprehensive surveillance system.

Asunto(s)

RESUMEN

The Countrywide Mortality Surveillance for Action platform is collecting verbal autopsy (VA) records from a nationally representative sample in Mozambique. These records are used to estimate the national and subnational cause-specific mortality fractions (CSMFs) for children (1-59 months) and neonates (1-28 days). Cross-tabulation of VA-based cause-of-death (COD) determination against that from the minimally invasive tissue sampling (MITS) from the Child Health and Mortality Prevention project revealed important misclassification errors for all the VA algorithms, which if not accounted for will lead to bias in the estimates of CSMF from VA. A recently proposed Bayesian VA-calibration method is used that accounts for this misclassification bias and produces calibrated estimates of CSMF. Both the VA-COD and the MITS-COD can be multi-cause (i.e., suggest more than one probable COD for some of the records). To fully use this probabilistic COD data, we use the multi-cause VA calibration. Two different computer-coded VA algorithms are considered-InSilicoVA and EAVA-and the final CSMF estimates are obtained using an ensemble calibration that uses data from both the algorithms. The calibrated estimates consistently offer a better fit to the data and reveal important changes in the CSMF for both children and neonates in Mozambique after accounting for VA misclassification bias.

Asunto(s)

RESUMEN

Mortality data, especially concerning deaths by cause, are critical for understanding the burden of disease, planning and monitoring of interventions aimed at reducing morbidity and mortality, as well as monitoring the Sustainable Development Goals for health (goal 3). In sub-Saharan Africa and most limited resource settings where burdens of diseases are high, there is a chronic lack of accurate and reliable data on mortality and causes of death. In these settings, complete diagnostic autopsy is only available in large hospitals and is unaffordable to most people. In addition, most deaths occur at the community level, and for facility deaths, physician medical certification of cause of death using medical information is not systematically completed. Available recent mortality and cause-of-death statistics are mostly based on modeling or periodic national surveys. Although they represent important tools, the uncertainty or long time intervals associated with their estimates challenge their use for precise or timely policy and program planning. Progressive efforts undertaken by low- and middle-income countries (LMICs) to revamp and expand their civil registration and vital statistics (CRVS) systems are commendable and timely. However, the time and resource needs in terms of infrastructure, technology, equipment, human resources, and demand creation to reach the entire population with a fully functional CRVS system are enormous and deprioritized in favor of more pressing demands in health care. The recent COVID-19 pandemic and emergence of epidemics across LMICs unveiled the vulnerabilities and challenges associated with the lack of or weak mortality data systems that can support planning, monitoring, and decision-making in these countries. In this context, building sustainable and resilient mortality surveillance systems that provide high-quality and timely mortality data represents a priority in Africa, as recently expressed in a newly developed continental framework for strengthening mortality surveillance in Africa by the Africa CDC.

Asunto(s)

RESUMEN

Verbal autopsies (VAs) are extensively used to determine cause of death (COD) in many low- and middle-income countries. However, COD determination from VA can be inaccurate. Computer coded verbal autopsy (CCVA) algorithms used for this task are imperfect and misclassify COD for a large proportion of deaths. If not accounted for, this misclassification leads to biased estimates of cause-specific mortality fractions (CSMFs), a critical piece in health-policy making. Recent work has demonstrated that the knowledge of the CCVA misclassification rates can be used to calibrate raw VA-based CSMF estimates to account for the misclassification bias. In this manuscript, we review the current practices and issues with raw COD predictions from CCVA algorithms and provide a complete primer on how to use the VA calibration approach with the calibratedVA software to correct for verbal autopsy misclassification bias in cause-specific mortality estimates. We use calibratedVA to obtain CSMFs for child (1-59 months) and neonatal deaths using VA data from the Countrywide Mortality Surveillance for Action project in Mozambique.

Asunto(s)

RESUMEN

INTRODUCTION: In 2018, Mozambique's Ministry of Health launched a guideline for a nationwide implementation of eight differentiated service delivery models to optimize HIV service delivery and achieve universal coverage of HIV care and treatment. The models were (1) Fast-track, (2) Three-month Antiretrovirals Dispensing, (3) Community Antiretroviral Therapy Groups, (4) Adherence Clubs, (5) Family-approach, and three one-stop shop models for (6) Tuberculosis, (7) Maternal and Child Health, and (8) Adolescent-friendly Health Services. This study identified drivers of implementation success and failure across these differentiated service delivery models. METHODS: Twenty in-depth individual interviews were conducted with managers and providers from the Ministry of Health and implementing partners from all levels of the health system between July and September 2021. National-level participants were based in the capital city of Maputo, and participants at provincial, district and health facility levels were from Sofala province, a purposively selected setting. The Consolidated Framework for Implementation Research (CFIR) guided data collection and thematic analysis. Deductively selected constructs were assessed while allowing for additional themes to emerge inductively. RESULTS: The CFIR constructs of Relative Advantage, Complexity, Patient Needs and Resources, and Reflecting and Evaluating were identified as drivers of implementation, whereas Available Resources and Access to Knowledge and Information were identified as barriers. Fast-track and Three-month Antiretrovirals Dispensing models were deemed easier to implement and more effective in reducing workload. Adherence Clubs and Community Antiretroviral Therapy Groups were believed to be less preferred by clients in urban settings. COVID-19 (an inductive theme) improved acceptance and uptake of individual differentiated service delivery models that reduced client visits, but it temporarily interrupted the implementation of group models. CONCLUSIONS: This study described important determinants to be addressed or leveraged for the successful implementation of differentiated service delivery models in Mozambique. The models were considered advantageous overall for the health system and clients when compared with the standard of care. However, successful implementation requires resources and ongoing training for frontline providers. COVID-19 expedited individual models by loosening the inclusion criteria; this experience can be leveraged to optimize the design and implementation of differentiated service delivery models in Mozambique and other countries.

Asunto(s)

RESUMEN

Mozambique reported the first case of coronavirus disease 2019 (COVID-19) in March 2020 and it has since spread to all provinces in the country. To investigate the introductions and spread of SARS-CoV-2 in Mozambique, 1 142 whole genome sequences sampled within Mozambique were phylogenetically analyzed against a globally representative set, reflecting the first 25 months of the epidemic. The epidemic in the country was marked by four waves of infection, the first associated with B.1 ancestral lineages, while the Beta, Delta, and Omicron Variants of Concern (VOCs) were responsible for most infections and deaths during the second, third, and fourth waves. Large-scale viral exchanges occurred during the latter three waves and were largely attributed to southern African origins. Not only did the country remain vulnerable to the introductions of new variants but these variants continued to evolve within the borders of the country. Due to the Mozambican health system already under constraint, and paucity of data in Mozambique, there is a need to continue to strengthen and support genomic surveillance in the country as VOCs and Variants of interests (VOIs) are often reported from the southern African region.

RESUMEN

In 2018, Mozambique's Ministry of Health launched a guideline for a nationwide implementation of eight differentiated service delivery models to optimize HIV service delivery and achieve universal coverage of HIV care and treatment. The models were (1) Fast­track, (2) Three­month Antiretrovirals Dispensing, (3) Community Antiretroviral Therapy Groups, (4) Adherence Clubs, (5) Family­approach, and three one­stop shop models for (6) Tuberculosis, (7) Maternal and Child Health, and (8) Adolescent­friendly Health Services. This study identified drivers of implementation success and failure across these differentiated service delivery models.

Asunto(s)

RESUMEN

Sub-Saharan Africa lacks timely, reliable, and accurate national data on mortality and causes of death (CODs). In 2018 Mozambique launched a sample registration system (Countrywide Mortality Surveillance for Action [COMSA]-Mozambique), which collects continuous birth, death, and COD data from 700 randomly selected clusters, a nationally representative population of 828,663 persons. Verbal and social autopsy interviews are conducted for COD determination. We analyzed data collected in 2019­2020 to report mortality rates and cause-specific fractions. Causespecific results were generated using computer-coded verbal autopsy (CCVA) algorithms for deaths among those age 5 years and older. For under-five deaths, the accuracy of CCVA results was increased through calibration with data from minimally invasive tissue sampling. Neonatal and under-five mortality rates were, respectively, 23 (95% CI: 18­28) and 80 (95% CI: 69­91) deaths per 1,000 live births. Mortality rates per 1,000 were 18 (95% CI: 14­21) among age 5­14 years, 26 (95% CI: 20­31) among age 15­24 years, 258 (95% CI: 230­287) among age 25­59 years, and 531 (95% CI: 490­572) among age 601 years. Urban areas had lower mortality rates than rural areas among children under 15 but not among adults. Deaths due to infections were substantial across all ages. Other predominant causes by age group were prematurity and intrapartum-related events among neonates; diarrhea, malaria, and lower respiratory infections among children 1­59 months; injury, malaria, and diarrhea among children 5­14 years; HIV, injury, and cancer among those age 15­59 years; and cancer and cardiovascular disease at age 601 years. The COMSA-Mozambique platform offers a rich and unique system for mortality and COD determination and monitoring and an opportunity to build a comprehensive surveillance system.

Asunto(s)

RESUMEN

We used publicly available data to describe epidemiology, genomic surveillance, and public health and social measures from the first 3 COVID-19 pandemic waves in southern Africa during April 6, 2020-September 19, 2021. South Africa detected regional waves on average 7.2 weeks before other countries. Average testing volume 244 tests/million/day) increased across waves and was highest in upper-middle-income countries. Across the 3 waves, average reported regional incidence increased (17.4, 51.9, 123.3 cases/1 million population/day), as did positivity of diagnostic tests (8.8%, 12.2%, 14.5%); mortality (0.3, 1.5, 2.7 deaths/1 million populaiton/day); and case-fatality ratios (1.9%, 2.1%, 2.5%). Beta variant (B.1.351) drove the second wave and Delta (B.1.617.2) the third. Stringent implementation of safety measures declined across waves. As of September 19, 2021, completed vaccination coverage remained low (8.1% of total population). Our findings highlight opportunities for strengthening surveillance, health systems, and access to realistically available therapeutics, and scaling up risk-based vaccination.

Asunto(s)

RESUMEN

We detected Bombali ebolavirus RNA in 3 free-tailed bats (Mops condylurus, Molossidae) in Mozambique. Sequencing of the large protein gene revealed 98% identity with viruses previously detected in Sierra Leone, Kenya, and Guinea. Our findings further support the suspected role of Mops condylurus bats in maintaining Bombali ebolavirus

Asunto(s)

RESUMEN

We detected Bombali ebolavirus RNA in 3 free-tailed bats (Mops condylurus, Molossidae) in Mozambique. Sequencing of the large protein gene revealed 98% identity with viruses previously detected in Sierra Leone, Kenya, and Guinea. Our findings further support the suspected role of Mops condylurus bats in maintaining Bombali ebolavirus.

Asunto(s)