One Health: navigating plague in Madagascar amidst COVID-19.

BACKGROUND: Africa sees the surge of plague cases in recent decades, with hotspots in the Democratic Republic of Congo, Madagascar, and Peru. A rodent-borne scourge, the bacterial infection known as plague is transmitted to humans via the sneaky bites of fleas, caused by Yersinia pestis. Bubonic plague has a case fatality rate of 20.8% with treatment, but in places such as Madagascar the mortality rate can increase to 40-70% without treatment. MAIN TEXT: Tragedy strikes in the Ambohidratrimo district as three lives are claimed by the plague outbreak and three more fight for survival in the hospitals, including one man in critical condition, from the Ambohimiadana, Antsaharasty, and Ampanotokana communes, bringing the total plague victims in the area to a grim to five. Presently, the biggest concern is the potential plague spread among humans during the ongoing COVID-19 pandemic. Effective disease control can be achieved through training and empowering local leaders and healthcare providers in rural areas, implementing strategies to reduce human-rodent interactions, promoting water, sanitation and hygiene practices (WASH) practices, and carrying out robust vector, reservoir and pest control, diversified animal surveillance along with human surveillance should be done to more extensively to fill the lacunae of knowledge regarding the animal to human transmission. The lack of diagnostic laboratories equipped represents a major hurdle in the early detection of plague in rural areas. To effectively combat plague, these tests must be made more widely available. Additionally, raising awareness among the general population through various means such as campaigns, posters and social media about the signs, symptoms, prevention, and infection control during funerals would greatly decrease the number of cases. Furthermore, healthcare professionals should be trained on the latest methods of identifying cases, controlling infections and protecting themselves from the disease. CONCLUSIONS: Despite being endemic to Madagascar, the outbreak's pace is unparalleled, and it may spread to non-endemic areas. The utilization of a One Health strategy that encompasses various disciplines is crucial for minimizing catastrophe risk, antibiotic resistance, and outbreak readiness. Collaboration across sectors and proper planning ensures efficient and consistent communication, risk management, and credibility during disease outbreaks.

Epidemiological Patterns of Seasonal Respiratory Viruses during the COVID-19 Pandemic in Madagascar, March 2020-May 2022.

Three epidemic waves of coronavirus disease-19 (COVID-19) occurred in Madagascar from March 2020 to May 2022, with a positivity rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) of 21% to 33%. Our study aimed to identify the impact of COVID-19 on the epidemiology of seasonal respiratory viruses (RVs) in Madagascar. We used two different specimen sources (SpS). First, 2987 nasopharyngeal (NP) specimens were randomly selected from symptomatic patients between March 2020 and May 2022 who tested negative for SARS-CoV-2 and were tested for 14 RVs by multiplex real-time PCR. Second, 6297 NP specimens were collected between March 2020 and May 2022 from patients visiting our sentinel sites of the influenza sentinel network. The samples were tested for influenza, respiratory syncytial virus (RSV), and SARS-CoV-2. From SpS-1, 19% (569/2987) of samples tested positive for at least one RV. Rhinovirus (6.3%, 187/2987) was the most frequently detected virus during the first two waves, whereas influenza predominated during the third. From SpS-2, influenza, SARS-CoV-2, and RSV accounted for 5.4%, 24.5%, and 39.4% of the detected viruses, respectively. During the study period, we observed three different RV circulation profiles. Certain viruses circulated sporadically, with increased activity in between waves of SARS-CoV-2. Other viruses continued to circulate regardless of the COVID-19 situation. Certain viruses were severely disrupted by the spread of SARS-CoV-2. Our findings underline the importance and necessity of maintaining an integrated disease surveillance system for the surveillance and monitoring of RVs of public health interest.

High seroprevalence of SARS-CoV-2 in Burkina-Faso, Ghana and Madagascar in 2021: a population-based study.

BACKGROUND: The current COVID-19 pandemic affects the entire world population and has serious health, economic and social consequences. Assessing the prevalence of COVID-19 through population-based serological surveys is essential to monitor the progression of the epidemic, especially in African countries where the extent of SARS-CoV-2 spread remains unclear. METHODS: A two-stage cluster population-based SARS-CoV-2 seroprevalence survey was conducted in Bobo-Dioulasso and in Ouagadougou, Burkina Faso, Fianarantsoa, Madagascar and Kumasi, Ghana between February and June 2021. IgG seropositivity was determined in 2,163 households with a specificity improved SARS-CoV-2 Enzyme-linked Immunosorbent Assay. Population seroprevalence was evaluated using a Bayesian logistic regression model that accounted for test performance and age, sex and neighbourhood of the participants. RESULTS: Seroprevalence adjusted for test performance and population characteristics were 55.7% [95% Credible Interval (CrI) 49·0; 62·8] in Bobo-Dioulasso, 37·4% [95% CrI 31·3; 43·5] in Ouagadougou, 41·5% [95% CrI 36·5; 47·2] in Fianarantsoa, and 41·2% [95% CrI 34·5; 49·0] in Kumasi. Within the study population, less than 6% of participants performed a test for acute SARS-CoV-2 infection since the onset of the pandemic. CONCLUSIONS: High exposure to SARS-CoV-2 was found in the surveyed regions albeit below the herd immunity threshold and with a low rate of previous testing for acute infections. Despite the high seroprevalence in our study population, the duration of protection from naturally acquired immunity remains unclear and new virus variants continue to emerge. This highlights the importance of vaccine deployment and continued preventive measures to protect the population at risk.

SARS-CoV-2 infection rate in Antananarivo frontline health care workers, Madagascar.

BACKGROUND: Health care workers (HCWs) represent a vulnerable population during epidemic periods. Our cohort study aimed to estimate the risk of infection and associated factors among HCWs during the first wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Madagascar. METHODS: A prospective cohort study was carried out in three hospitals that oversaw the first cases of COVID-19. Monthly ELISA-based serological tests were conducted, and nasopharyngeal swabs were collected in the case of symptoms linked to COVID-19 for RT-PCR analysis. Survival analyses were used to determine factors associated with SARS-CoV-2 infection. RESULTS: The study lasted 7 months from May 2020. We included 122 HCWs, 61.5% of whom were women. The median age was 31.9 years (IQR: 26.4-42.3). In total, 42 (34.4%) had SARS-CoV-2 infections, of which 20 were asymptomatic (47.6%). The incidence of SARS-CoV-2 infection was 9.3% (95% CI [6.5-13.2]) person-months. Sixty-five HCWs presented symptoms, of which 19 were positive by RT-PCR. When adjusted for exposure to deceased cases, infection was more frequent in HCWs younger than 30 years of age (RR = 4.9, 95% CI [1.4-17.2]). CONCLUSION: Our results indicate a high incidence of infection with SARS-CoV-2 among HCWs, with a high proportion of asymptomatic cases. Young HCWs are more likely to be at risk than others. Greater awareness among young people is necessary to reduce the threat of infection among HCWs.

Prioritizing COVID-19 vaccination efforts and dose allocation within Madagascar.

BACKGROUND: While mass COVID-19 vaccination programs are underway in high-income countries, limited availability of doses has resulted in few vaccines administered in low and middle income countries (LMICs). The COVID-19 Vaccines Global Access (COVAX) is a WHO-led initiative to promote vaccine access equity to LMICs and is providing many of the doses available in these settings. However, initial doses are limited and countries, such as Madagascar, need to develop prioritization schemes to maximize the benefits of vaccination with very limited supplies. There is some consensus that dose deployment should initially target health care workers, and those who are more vulnerable including older individuals. However, questions of geographic deployment remain, in particular associated with limits around vaccine access and delivery capacity in underserved communities, for example in rural areas that may also include substantial proportions of the population. METHODS: To address these questions, we developed a mathematical model of SARS-CoV-2 transmission dynamics and simulated various vaccination allocation strategies for Madagascar. Simulated strategies were based on a number of possible geographical prioritization schemes, testing sensitivity to initial susceptibility in the population, and evaluating the potential of tests for previous infection. RESULTS: Using cumulative deaths due to COVID-19 as the main outcome of interest, our results indicate that distributing the number of vaccine doses according to the number of elderly living in the region or according to the population size results in a greater reduction of mortality compared to distributing doses based on the reported number of cases and deaths. The benefits of vaccination strategies are diminished if the burden (and thus accumulated immunity) has been greatest in the most populous regions, but the overall strategy ranking remains comparable. If rapid tests for prior immunity may be swiftly and effectively delivered, there is potential for considerable gain in mortality averted, but considering delivery limitations modulates this. CONCLUSION: At a subnational scale, our results support the strategy adopted by the COVAX initiative at a global scale.

The impact of COVID-19 on clinical research for Neglected Tropical Diseases (NTDs): A case study of bubonic plague.

BACKGROUND: Among the many collaterals of the COVID-19 pandemic is the disruption of health services and vital clinical research. COVID-19 has magnified the challenges faced in research and threatens to slow research for urgently needed therapeutics for Neglected Tropical Diseases (NTDs) and diseases affecting the most vulnerable populations. Here we explore the impact of the pandemic on a clinical trial for plague therapeutics and strategies that have been considered to ensure research efforts continue. METHODS: To understand the impact of the COVID-19 pandemic on the trial accrual rate, we documented changes in patterns of all-cause consultations that took place before and during the pandemic at health centres in two districts of the Amoron'I Mania region of Madagascar where the trial is underway. We also considered trends in plague reporting and other external factors that may have contributed to slow recruitment. RESULTS: During the pandemic, we found a 27% decrease in consultations at the referral hospital, compared to an 11% increase at peripheral health centres, as well as an overall drop during the months of lockdown. We also found a nation-wide trend towards reduced number of reported plague cases. DISCUSSION: COVID-19 outbreaks are unlikely to dissipate in the near future. Declining NTD case numbers recorded during the pandemic period should not be viewed in isolation or taken as a marker of things to come. It is vitally important that researchers are prepared for a rebound in cases and, most importantly, that research continues to avoid NTDs becoming even more neglected.

Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar.

As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (Ct) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-Ct value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on Ct value, suggesting that Ct value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level Ct distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional Ct distributions across three regions in Madagascar. We find that Ct-derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of Ct values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.

Surge of Typhoid Intestinal Perforations as Possible Result of COVID-19-Associated Delays in Seeking Care, Madagascar.

During the coronavirus disease pandemic, we observed a 6.4-fold increase in typhoid intestinal perforation incidence in Antananarivo, Madagascar. Thirteen perforations occurred within 6 months (February 2020-July 2020), compared with 13 perforations during the previous 41 months (August 2016-January 2020). The increase may be attributable to delayed healthcare seeking during the pandemic.

Household transmission of COVID-19 among the earliest cases in Antananarivo, Madagascar.

BACKGROUND: Households are among the highest risk for the transmission of SARS-CoV-2. In sub-Saharan Africa, very few studies have described household transmission during the COVID-19 pandemic. Our work aimed to describe the epidemiologic parameters and analyze the secondary attack rate (SAR) in Antananarivo, Madagascar, following the introduction of SARS-CoV-2 in the country in March 2020. METHODS: A prospective case-ascertained study of all identified close contacts of laboratory-confirmed COVID-19 infections was conducted in Antananarivo from March to June 2020. Cases and household contacts were followed for 21 days. We estimated epidemic parameters of disease transmission by fitting parametric distributions based on infector-infected paired data. We assessed factors influencing transmission risk by analyzing the SAR. FINDINGS: Overall, we included 96 index cases and 179 household contacts. Adjusted with the best-fit normal distribution, the incubation period was 4.1 days (95% CI 0.7-7.5]). The serial interval was 6.0 days (95% CI [2.4-9.6]) after adjusting with the best-fit Weibull distribution. On average, each index case infected 1.6 family members (95%CI [0.9-2.3]). The mean SAR among close contacts was 38.8% (95% CI [19.5-58.2]) with the best-fit gamma distribution. Contacts older than 35 years old were more likely to be infected, and the highest SAR was found among them. CONCLUSION: The results of our study provide key insights into the epidemiology of the first wave of SARS-CoV-2 in Madagascar. High rates of household transmission were found in Antananarivo, emphasizing the need for preventive measures to reduce community transmission.

Integrating Health Systems and Science to Respond to COVID-19 in a Model District of Rural Madagascar.

There are many outstanding questions about how to control the global COVID-19 pandemic. The information void has been especially stark in the World Health Organization Africa Region, which has low per capita reported cases, low testing rates, low access to therapeutic drugs, and has the longest wait for vaccines. As with all disease, the central challenge in responding to COVID-19 is that it requires integrating complex health systems that incorporate prevention, testing, front line health care, and reliable data to inform policies and their implementation within a relevant timeframe. It requires that the population can rely on the health system, and decision-makers can rely on the data. To understand the process and challenges of such an integrated response in an under-resourced rural African setting, we present the COVID-19 strategy in Ifanadiana District, where a partnership between Malagasy Ministry of Public Health (MoPH) and non-governmental organizations integrates prevention, diagnosis, surveillance, and treatment, in the context of a model health system. These efforts touch every level of the health system in the district-community, primary care centers, hospital-including the establishment of the only RT-PCR lab for SARS-CoV-2 testing outside of the capital. Starting in March of 2021, a second wave of COVID-19 occurred in Madagascar, but there remain fewer cases in Ifanadiana than for many other diseases (e.g., malaria). At the Ifanadiana District Hospital, there have been two deaths that are officially attributed to COVID-19. Here, we describe the main components and challenges of this integrated response, the broad epidemiological contours of the epidemic, and how complex data sources can be developed to address many questions of COVID-19 science. Because of data limitations, it still remains unclear how this epidemic will affect rural areas of Madagascar and other developing countries where health system utilization is relatively low and there is limited capacity to diagnose and treat COVID-19 patients. Widespread population based seroprevalence studies are being implemented in Ifanadiana to inform the COVID-19 response strategy as health systems must simultaneously manage perennial and endemic disease threats.

SARS-CoV-2 antibody seroprevalence follow-up in Malagasy blood donors during the 2020 COVID-19 Epidemic.

BACKGROUND: The incidence of the 2020 COVID-19 epidemic in Africa seems to be different from that of the rest of the world, however its true extent is probably underestimated. Conducting population based sero-surveys during the epidemic has moreover been extremely challenging, driving our group and others to study blood donor samples. METHODS: We collected regional epidemiological COVID-19 surveillance data, and simultaneously monitored anti-SARS-CoV-2 antibody seroprevalences monthly throughout the epidemic in 5 major Region-associated Blood Transfusion Centres of Madagascar over a period of 9 months. FINDINGS: Soon after attaining the first epidemic peaks between May and August 2020, both crude and population-weighted test-performance-adjusted seroprevalences of anti-SARS-CoV-2 antibodies was in Malagasy blood donors rapidly increased up to over 40% positivity. INTERPRETATION: These findings suggest a high cumulative incidence of infection and seroconversion, which may have contributed to the observed deceleration of infection rates, but was not sufficient to prevent the second epidemic wave that struck Madagascar in Spring 2021. FUNDING: This project was funded by the United States Agency for International Development.

First Prototype of the Infectious Diseases Seeker (IDS) Software for Prompt Identification of Infectious Diseases.

The rapid detection of ongoing outbreak - and the identification of causative pathogen - is pivotal for the early recognition of public health threats. The emergence and re-emergence of infectious diseases are linked to several determinants, both human factors - such as population density, travel, and trade - and ecological factors - like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens [e.g. real-time polymerase chain reaction (PCR)], and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. The study aims to integrate the current prevention and control system with a prediction tool for infectious diseases, based on regression analysis, to support decision makers, health care workers, and first responders to quickly and properly recognise an outbreak. This study has the intention to develop an infectious disease regressive prediction tool working with an off-line database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool has been developed as a first prototype of a software solution called Infectious Diseases Seeker (IDS) and it had been established in two main steps, the database building stage and the software implementation stage (MATLAB® environment). The IDS has been tested with the epidemiological data of three outbreaks occurred recently: severe acute respiratory syndrome epidemic in China (2002-2003), plague outbreak in Madagascar (2017) and the Ebola virus disease outbreak in the Democratic Republic of Congo (2018). The outcomes are promising and they reveal that the software has been able to recognize and characterize these outbreaks. The future perspective about this software regards the developing of that tool as a useful and user-friendly predictive tool appropriate for first responders, health care workers, and public health decision makers to help them in predicting, assessing and contrasting outbreaks.

The COVID-19 epidemic in Madagascar: clinical description and laboratory results of the first wave, march-september 2020.

BACKGROUND: Following the first detection of SARS-CoV-2 in passengers arriving from Europe on 19 March 2020, Madagascar took several mitigation measures to limit the spread of the virus in the country. METHODS: Nasopharyngeal and/or oropharyngeal swabs were collected from travellers to Madagascar, suspected SARS-CoV-2 cases and contact of confirmed cases. Swabs were tested at the national reference laboratory using real-time RT-PCR. Data collected from patients were entered in an electronic database for subsequent statistical analysis. All distribution of laboratory-confirmed cases were mapped, and six genomes of viruses were fully sequenced. RESULTS: Overall, 26,415 individuals were tested for SARS-CoV-2 between 18 March and 18 September 2020, of whom 21.0% (5,553/26,145) returned positive. Among laboratory-confirmed SARS-CoV-2-positive patients, the median age was 39 years (IQR: 28-52), and 56.6% (3,311/5,553) were asymptomatic at the time of sampling. The probability of testing positive increased with age with the highest adjusted odds ratio of 2.2 [95% CI: 1.9-2.5] for individuals aged 49 years and more. Viral strains sequenced belong to clades 19A, 20A and 20B indicative of several independent introduction of viruses. CONCLUSIONS: Our study describes the first wave of the COVID-19 in Madagascar. Despite early strategies in place Madagascar could not avoid the introduction and spread of the virus. More studies are needed to estimate the true burden of disease and make public health recommendations for a better preparation to another wave.

Scrutinizing the spread of COVID-19 in Madagascar.

We scrutinize the evolution of COVID-19 in Madagascar by comparing results from three approaches (cubic polynomial, semi-gaussian and gaussian-like models) which we use to provide an analytical form of the spread of the pandemic. In so doing, we introduce (for the first time) the ratio ℜI/Tc,d of the cumulative and daily numbers of infected persons over the corresponding one of tests which are expected to be less sensitive to the number of the tests because the credibility of the results based only on the absolute numbers often raises some criticisms. We also give and compare the effective reproduction number Reff from different approaches and with the ones of some European countries with a small number of population (Greece, Switzerland) and some other African countries. Finally, we show and comment the evolution of the total number of deaths and of the per cent number of cured persons and discuss the performance of the medical care.

Monitoring for outbreak-associated excess mortality in an African city: Detection limits in Antananarivo, Madagascar.

OBJECTIVES: Quantitative estimates of the impact of infectious disease outbreaks are required to develop measured policy responses. In many low- and middle-income countries, inadequate surveillance and incompleteness of death registration are important barriers. DESIGN: Here, we characterize how large an impact on mortality would have to be for being detectable using the uniquely detailed mortality notification data from the city of Antananarivo, Madagascar, with application to a recent measles outbreak. RESULTS: The weekly mortality rate of children during the 2018-2019 measles outbreak was 161% above the expected value at its peak, and the signal can be detected earlier in children than in the general population. This approach to detect anomalies from expected baseline mortality allows us to delineate the prevalence of COVID-19 at which excess mortality would be detectable with the existing death notification system in Antananarivo. CONCLUSIONS: Given current age-specific estimates of the COVID-19 fatality ratio and the age structure of the population in Antananarivo, we estimate that as few as 11 deaths per week in the 60-70 years age group (corresponding to an infection rate of approximately 1%) would detectably exceed the baseline. Data from 2020 will undergo necessary processing and quality control in the coming months. Our results provide a baseline for interpreting this information.

Reconciling model predictions with low reported cases of COVID-19 in Sub-Saharan Africa: insights from Madagascar.

COVID-19 has wreaked havoc globally with particular concerns for sub-Saharan Africa (SSA), where models suggest that the majority of the population will become infected. Conventional wisdom suggests that the continent will bear a higher burden of COVID-19 for the same reasons it suffers from other infectious diseases: ecology, socio-economic conditions, lack of water and sanitation infrastructure, and weak health systems. However, so far SSA has reported lower incidence and fatalities compared to the predictions of standard models and the experience of other regions of the world. There are three leading explanations, each with different implications for the final epidemic burden: (1) low case detection, (2) differences in epidemiology (e.g. low R 0 ), and (3) policy interventions. The low number of cases have led some SSA governments to relaxing these policy interventions. Will this result in a resurgence of cases? To understand how to interpret the lower-than-expected COVID-19 case data in Madagascar, we use a simple age-structured model to explore each of these explanations and predict the epidemic impact associated with them. We show that the incidence of COVID-19 cases as of July 2020 can be explained by any combination of the late introduction of first imported cases, early implementation of non-pharmaceutical interventions (NPIs), and low case detection rates. We then re-evaluate these findings in the context of the COVID-19 epidemic in Madagascar through August 2020. This analysis reinforces that Madagascar, along with other countries in SSA, remains at risk of a growing health crisis. If NPIs remain enforced, up to 50,000 lives may be saved. Even with NPIs, without vaccines and new therapies, COVID-19 could infect up to 30% of the population, making it the largest public health threat in Madagascar for the coming year, hence the importance of clinical trials and continually improving access to healthcare.