Excess mortality associated with the COVID-19 pandemic during the 2020 and 2021 waves in Antananarivo, Madagascar.

INTRODUCTION: COVID-19-associated mortality remains difficult to estimate in sub-Saharan Africa because of the lack of comprehensive systems of death registration. Based on death registers referring to the capital city of Madagascar, we sought to estimate the excess mortality during the COVID-19 pandemic and calculate the loss of life expectancy. METHODS: Death records between 2016 and 2021 were used to estimate weekly excess mortality during the pandemic period. To infer its synchrony with circulation of SARS-CoV-2, a cross-wavelet analysis was performed. Life expectancy loss due to the COVID-19 pandemic was calculated by projecting mortality rates using the Lee and Carter model and extrapolating the prepandemic trends (1990-2019). Differences in life expectancy at birth were disaggregated by cause of death. RESULTS: Peaks of excess mortality in 2020-21 were associated with waves of COVID-19. Estimates of all-cause excess mortality were 38.5 and 64.9 per 100 000 inhabitants in 2020 and 2021, respectively, with excess mortality reaching ≥50% over 6 weeks. In 2021, we quantified a drop of 0.8 and 1.0 years in the life expectancy for men and women, respectively attributable to increased risks of death beyond the age of 60 years. CONCLUSION: We observed high excess mortality during the pandemic period, in particular around the peaks of SARS-CoV-2 circulation in Antananarivo. Our study highlights the need to implement death registration systems in low-income countries to document true toll of a pandemic.

Identification of factors associated with residual malaria transmission using school-based serological surveys in settings pursuing elimination.

BACKGROUND: Targeted research on residual malaria transmission is important to improve strategies in settings pursuing elimination, where transmission reductions prove challenging. This study aimed to detect and characterize spatial heterogeneity and factors associated with Plasmodium falciparum infections and exposure, P. falciparum apical membrane antigen 1 (PfAMA1) antibody (Ab) response, in the Central Highlands of Madagascar (CHL). METHODS: From May to July 2014, a cross-sectional school-based survey was carried out in 182 fokontany (villages) within 7 health districts of the CHL. Rapid diagnostic tests (RDTs) and a bead-based immunoassay including PfAMA1 antigen biomarker were used to estimate malaria prevalence and seroprevalence, respectively. Local Moran's I index was used to detect spatial "hotspots". Remotely sensed environmental data-temperature, vegetation indices, land covers, and elevation-were used in multivariable mixed-effects logistic regression models to characterize factors associated with malaria infection and cumulative exposure. RESULTS: Among 6,293 school-children ages 2-14 years surveyed, RDT prevalence was low at 0.8% (95% CI 0.6-1.1%), while PfAMA1 Ab seroprevalence was 7.0% (95% CI 6.4-7.7%). Hotspots of PfAMA1 Ab seroprevalence were observed in two districts (Ankazobe and Mandoto). Seroprevalence increased for children living > 5 km from a health centre (adjusted odds ratio (OR) = 1.6, 95% CI 1.2-2.2), and for those experiencing a fever episode in the previous 2 weeks (OR 1.7, 95% CI 1.2-2.4), but decreased at higher elevation (for each 100-m increase, OR = 0.7, 95% CI 0.6-0.8). A clear age pattern was observed whereby children 9-10 years old had an OR of 1.8 (95% CI 1.2-2.4), children 11-12 years an OR of 3.7 (95% CI 2.8-5.0), and children 13-14 years an OR of 5.7 (95% CI 4.0-8.0) for seropositivity, compared with younger children (2-8 years). CONCLUSION: The use of serology in this study provided a better understanding of malaria hotspots and associated factors, revealing a pattern of higher transmission linked to geographical barriers in health care access. The integration of antibody-assays into existing surveillance activities could improve exposure assessment, and may help to monitor the effectiveness of malaria control efforts and adapt elimination interventions.

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.

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 (C t ) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-C t 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 C t value, suggesting that C t 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 C t 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 C t distributions across three regions in Madagascar. We find that C t -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 C t 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.

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.

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.

School-Based Serosurveys to Assess the Validity of Using Routine Health Facility Data to Target Malaria Interventions in the Central Highlands of Madagascar.

BACKGROUND: In low-malaria-transmission areas of Madagascar, annual parasite incidence (API) from routine data has been used to target indoor residual spraying at subdistrict commune level. To assess validity of this approach, we conducted school-based serological surveys and health facility (HF) data quality assessments in 7 districts to compare API to gold-standard commune-level serological measures. METHODS: At 2 primary schools in each of 93 communes, 60 students were randomly selected with parents and teachers. Capillary blood was drawn for rapid diagnostic tests (RDTs) and serology. Multiplex bead-based immunoassays to detect antibodies to 5 Plasmodium falciparum antigens were conducted, and finite mixture models used to characterize seronegative and seropositive populations. Reversible catalytic models generated commune-level annual seroconversion rates (SCRs). HF register data were abstracted to assess completeness and accuracy. RESULTS: RDT positivity from 12 770 samples was 0.5%. Seroprevalence to tested antigens ranged from 17.9% (MSP-1) to 59.7% (PF13). Median commune-level SCR was 0.0108 (range, 0.001-0.075). Compared to SCRs, API identified 71% (95% confidence interval, 51%-87%) of the 30% highest-transmission communes; sensitivity declined at lower levels. Routine data accuracy did not substantially affect API performance. CONCLUSIONS: API performs reasonably well at identifying higher-transmission communes but sensitivity declined at lower transmission levels.

The impact of rainfall on drinking water quality in Antananarivo, Madagascar.

Low-income cities that are subject to high population pressure and vulnerable to climate events often have a low capacity to continuously deliver safe drinking water. Here we reported the results of a 32-year survey on the temporal dynamics of drinking water quality indicators in the city of Antananarivo. We analyzed the long-term evolution of the quality of the water supplied and characterized the interactions between climatic conditions and the full-scale water supply system. A total of 25,467 water samples were collected every week at different points in the supplied drinking water system. Samples were analyzed for total coliforms (TC), Escherichia coli (EC), intestinal Enterococci (IE), and Spores of Sulphite-Reducing Clostridia (SSRC). Nine-hundred-eighty-one samples that were identified as positive for one or more indicators were unevenly distributed over time. The breakpoint method identified four periods when the time series displayed changes in the level and profile of contamination (i) and the monthly pattern of contamination (ii), with more direct effects of rainfall on the quality of supplied drinking water. The modeling showed significantly different lags among indicators of bacteria occurrence after cumulative rainfall, which range from 4 to 8 weeks. Among the effects of low-income urbanization, a rapid demographic transition and the degradation of urban watersheds have gradually affected the quality of the water supplied and resulted in the more direct effects of rainfall events. We focused on the need to adopt an alternative perspective of drinking water and urban watersheds management.

Epidemiological characteristics of an urban plague epidemic in Madagascar, August-November, 2017: an outbreak report.

BACKGROUND: Madagascar accounts for 75% of global plague cases reported to WHO, with an annual incidence of 200-700 suspected cases (mainly bubonic plague). In 2017, a pneumonic plague epidemic of unusual size occurred. The extent of this epidemic provides a unique opportunity to better understand the epidemiology of pneumonic plagues, particularly in urban settings. METHODS: Clinically suspected plague cases were notified to the Central Laboratory for Plague at Institut Pasteur de Madagascar (Antananarivo, Madagascar), where biological samples were tested. Based on cases recorded between Aug 1, and Nov 26, 2017, we assessed the epidemiological characteristics of this epidemic. Cases were classified as suspected, probable, or confirmed based on the results of three types of diagnostic tests (rapid diagnostic test, molecular methods, and culture) according to 2006 WHO recommendations. FINDINGS: 2414 clinically suspected plague cases were reported, including 1878 (78%) pneumonic plague cases, 395 (16%) bubonic plague cases, one (<1%) septicaemic case, and 140 (6%) cases with unspecified clinical form. 386 (21%) of 1878 notified pneumonic plague cases were probable and 32 (2%) were confirmed. 73 (18%) of 395 notified bubonic plague cases were probable and 66 (17%) were confirmed. The case fatality ratio was higher among confirmed cases (eight [25%] of 32 cases) than probable (27 [8%] of 360 cases) or suspected pneumonic plague cases (74 [5%] of 1358 cases) and a similar trend was seen for bubonic plague cases (16 [24%] of 66 confirmed cases, four [6%] of 68 probable cases, and six [2%] of 243 suspected cases). 351 (84%) of 418 confirmed or probable pneumonic plague cases were concentrated in Antananarivo, the capital city, and Toamasina, the main seaport. All 50 isolated Yersinia pestis strains were susceptible to the tested antibiotics. INTERPRETATION: This predominantly urban plague epidemic was characterised by a large number of notifications in two major urban areas and an unusually high proportion of pneumonic forms, with only 23% having one or more positive laboratory tests. Lessons about clinical and biological diagnosis, case definition, surveillance, and the logistical management of the response identified in this epidemic are crucial to improve the response to future plague outbreaks. FUNDING: US Agency for International Development, WHO, Institut Pasteur, US Department of Health and Human Services, Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases, Models of Infectious Disease Agent Study of the National Institute of General Medical Sciences, AXA Research Fund, and the INCEPTION programme.

Estimating sources and sinks of malaria parasites in Madagascar.

In areas where malaria epidemiology is spatially and temporally heterogeneous, human-mediated parasite importation can result in non-locally acquired clinical cases and outbreaks in low-transmission areas. Using mobility estimates derived from the mobile phone data and spatial malaria prevalence data, we identify travel routes relevant to malaria transmission in Madagascar. We find that the primary hubs of parasite importation are in a spatially connected area of the central highlands. Surprisingly, sources of these imported infections are not spatially clustered. We then related these source locations directly to clinical cases in the low-transmission area of the capital. We find that in the capital, a major sink, the primary sources of infection are along the more populated coastal areas, although these sources are seasonally variable. Our results have implications for targeting interventions at source locations to achieve local or national malaria control goals.

Spatial and temporal dynamics of malaria in Madagascar.

BACKGROUND: Malaria is one of the primary health concerns in Madagascar. Based on the duration and intensity of transmission, Madagascar is divided into five epidemiological strata that range from low to mesoendemic transmission. In this study, the spatial and temporal dynamics of malaria within each epidemiological zone were studied. METHODS: The number of reported cases of uncomplicated malaria from 112 health districts between 2010 and 2014 were compiled and analysed. First, a Standardized Incidence Ratio was calculated to detect districts with anomalous incidence compared to the stratum-level incidence. Building on this, spatial and temporal malaria clusters were identified throughout the country and their variability across zones and over time was analysed. RESULTS: The incidence of malaria increased from 2010 to 2014 within each stratum. A basic analysis showed that districts with more than 50 cases per 1000 inhabitants are mainly located in two strata: East and West. Lower incidence values were found in the Highlands and Fringe zones. The standardization method revealed that the number of districts with a higher than expected numbers of cases increased through time and expanded into the Highlands and Fringe zones. The cluster analysis showed that for the endemic coastal region, clusters of districts migrated southward and the incidence of malaria was the highest between January and July with some variation within strata. CONCLUSION: This study identified critical districts with low incidence that shifted to high incidence and district that were consistent clusters across each year. The current study provided a detailed description of changes in malaria epidemiology and can aid the national malaria programme to reduce and prevent the expansion of the disease by targeting the appropriate areas.

Pneumonic Plague Transmission, Moramanga, Madagascar, 2015.

During a pneumonic plague outbreak in Moramanga, Madagascar, we identified 4 confirmed, 1 presumptive, and 9 suspected plague case-patients. Human-to-human transmission among close contacts was high (reproductive number 1.44) and the case fatality rate was 71%. Phylogenetic analysis showed that the Yersinia pestis isolates belonged to group q3, different from the previous outbreak.