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Background Malaria is one of the greatest recurring threats to public health in Mozambique with approximately 10 million cases and thousands of deaths reported annually. Although a malaria early warning system is being established in the country, it is focused on short-term (4–8 week) prediction windows. Increased understanding of the links between quasi-predictable interannual climate variability and malaria could lengthen the lead time for the malaria early warning system and enhance planning and actionable mitigation efforts by public health officials in the country. Methods To identify patterns of interannual variability, we did two principal component analyses of processed weekly district-level malaria incidences for the period 2010–17 in Mozambique and southern Africa regional precipitation for the period 1981–2019. We also did linear regression analyses of sea surface temperatures onto a precipitation index, and composites of various climate variables to establish links between precipitation and modes of climate variability. Findings Two dominant spatiotemporal patterns collectively account for 81% of the interannual variability of malaria in Mozambique. These patterns consisted of a primary hotspot over the central and southern part of the country and a secondary hotspot over the northern third of the country. We found these patterns to be closely related to precipitation variability driven by climate phenomena: the El Nino-Southern Oscillation and the Subtropical Indian Ocean Dipole. Interpretation Quasi-predictable global and regional climate phenomena influence regional precipitation over southern Africa. Knowledge of these associations can inform an enhancement of the malaria early warning system in Mozambique by lengthening early warning lead times. Similar analyses are possible for other countries whose climate is dominated by tropical modes of climate variability. Funding None.

Malaria is among the greatest public health threats in Mozambique, with over 10 million cases reported annually since 2018. Although the relationship between seasonal trends in environmental parameters and malaria cases is well established, the role of climate in deviations from the annual cycle is less clear. To investigate this and the potential for leveraging inter‐annual climate variability to predict malaria outbreaks, weekly district‐level malaria incidence spanning 2010–2017 were processed for a cross‐analysis with climate data. An empirical orthogonal function analysis of district‐level malaria incidence revealed two dominant spatiotemporal modes that collectively account for 81% of the inter‐annual variability of malaria: a mode dominated by variance over the southern half of Mozambique (64%), and another dominated by variance in the northern third of the country (17%). These modes of malaria variability are shown to be closely related to precipitation. Linear regression of global sea surface temperatures onto local precipitation indices over these variance maxima links the leading mode of inter‐annual malarial variability to the El Niño‐Southern Oscillation, such that La Niña leads to wetter conditions over southern Mozambique and, therefore, higher malaria prevalence. Similar analysis of spatiotemporal patterns of precipitation over a longer time period (1979–2019) indicate that the Subtropical Indian Ocean Dipole is both a strong predictor of regional precipitation and the climatic mechanism underlying the second mode of malarial variability. These results suggest that skillful malaria early warning systems may be developed that leverage quasi‐predictable modes of inter‐annual climate variability in the tropical oceans.

Background Multiplex bead assays (MBA) that measure IgG antibodies to the carboxy-terminal 19-kDa sub-unit of the merozoite surface protein 1 (MSP119) are currently used to determine malaria seroprevalence in human populations living in areas with both stable and unstable transmission. However, the species specificities of the IgG antibody responses to the malaria MSP119 antigens have not been extensively characterized using MBA. Methods Recombinant Plasmodium falciparum (3D7), Plasmodium malariae (China I), Plasmodium ovale (Nigeria I), and Plasmodium vivax (Belem) MSP119 proteins were covalently coupled to beads for MBA. Threshold cut-off values for the assays were estimated using sera from US citizens with no history of foreign travel and by receiver operator characteristic curve analysis using diagnostic samples. Banked sera from experimentally infected chimpanzees, sera from humans from low transmission regions of Haiti and Cambodia (N = 12), and elutions from blood spots from humans selected from a high transmission region of Mozambique (N = 20) were used to develop an antigen competition MBA for antibody cross-reactivity studies. A sub-set of samples was further characterized using antibody capture/elution MBA, IgG subclass determination, and antibody avidity measurement. Results Total IgG antibody responses in experimentally infected chimpanzees were species specific and could be completely suppressed by homologous competitor protein at a concentration of 10 μg/ml. Eleven of 12 samples from the low transmission regions and 12 of 20 samples from the high transmission area had antibody responses that were completely species specific. For 7 additional samples, the P. falciparum MSP119 responses were species specific, but various levels of incomplete heterologous competition were observed for the non-P. falciparum assays. A pan-malaria MSP119 cross-reactive antibody response was observed in elutions of blood spots from two 20–30 years old Mozambique donors. The antibody response from one of these two donors had low avidity and skewed almost entirely to the IgG3 subclass. Conclusions Even when P. falciparum, P. malariae, P. ovale, and P. vivax are co-endemic in a high transmission setting, most antibody responses to MSP119 antigens are species-specific and are likely indicative of previous infection history. True pan-malaria cross-reactive responses were found to occur rarely. Electronic supplementary material The online version of this article (10.1186/s12936-018-2566-0) contains supplementary material, which is available to authorized users.

Diarrheal diseases are a leading cause of morbidity and mortality in Africa. Although research documents the magnitude and pattern of diarrheal diseases are associated with weather in particular locations, there is limited quantification of this association in sub-Saharan Africa and no studies conducted in Mozambique. Our study aimed to determine whether variation in diarrheal disease was associated with precipitation in Mozambique. In secondary analyses we investigated the associations between temperature and diarrheal disease. We obtained weekly time series data for weather and diarrheal disease aggregated at the administrative district level for 1997–2014. Weather data include modeled estimates of precipitation and temperature. Diarrheal disease counts are confirmed clinical episodes reported to the Mozambique Ministry of Health (n = 7,315,738). We estimated the association between disease counts and precipitation, defined as the number of wet days (precipitation > 1 mm) per week, for the entire country and for Mozambique’s four regions. We conducted time series regression analyses using an unconstrained distributed lag Poisson model adjusted for time, maximum temperature, and district. Temperature was similarly estimated with adjusted covariates. Using a four-week lag, chosen a priori, precipitation was associated with diarrheal disease. One additional wet day per week was associated with a 1.86% (95% CI: 1.05–2.67%), 1.37% (95% CI: 0.70–2.04%), 2.09% (95% CI: 1.01–3.18%), and 0.63% (95% CI: 0.11–1.14%) increase in diarrheal disease in Mozambique’s northern, central, southern, and coastal regions, respectively. Our study indicates a strong association between diarrheal disease and precipitation. Diarrheal disease prevention efforts should target areas forecast to experience increased rainfall. The burden of diarrheal disease may increase with increased precipitation associated with climate change, unless additional health system interventions are undertaken.

OBJECTIVE: Universal coverage with insecticide-treated bed nets is a cornerstone of modern malaria control. Mozambique has developed a novel bed net allocation strategy, where the number of bed nets allocated per household is calculated on the basis of household composition and assumptions about who sleeps with whom. We set out to evaluate the performance of the novel allocation strategy. METHODS: 1,994 households were visited during household surveys following two universal coverage bed net distribution campaigns in Sofala and Nampula Provinces in 2010-2013. Each sleeping space was observed for the presence of a bed net, and the sleeping patterns for each household were recorded. The observed coverage and efficiency were compared to a simulated coverage and efficiency had conventional allocation strategies been used. A composite indicator, the product of coverage and efficiency, was calculated. Observed sleeping patterns were compared with the sleeping pattern assumptions. RESULTS: In households reached by the campaign, 93% (95% CI: 93-94%) of sleeping spaces in Sofala and 84% (82-86%) in Nampula were covered by campaign bed nets. The achieved efficiency was high, with 92% (91-93%) of distributed bed nets in Sofala and 93% (91-95%) in Nampula covering a sleeping space. Using the composite indicator, the novel allocation strategy outperformed all conventional strategies in Sofala and was tied for best in Nampula. The sleeping pattern assumptions were completely satisfied in 66% of households in Sofala and 56% of households in Nampula. The most common violation of the sleeping pattern assumptions was that male children 3-10 years of age tended not to share sleeping spaces with female children 3-10 or 10-16 years of age. CONCLUSIONS: The sleeping pattern assumptions underlying the novel bed net allocation strategy are generally valid, and net allocation using these assumptions can achieve high coverage and compare favorably with conventional allocation strategies. This article is protected by copyright. All rights reserved.

To examine human gene expression during uncomplicatedP. falciparummalaria, we obtained three samples (acute illness, treatment, and recovery) from 10 subjects and utilized each subject’s recovery sample as their baseline. At the time of acute illness (day 1), subjects had upregulation of innate immune response, cytokine, and inflammation-related genes (IL-1β, IL-6, TNF, and IFN-γ), which was more frequent with parasitemias>100,000 perμL and body temperatures≥39∘C. Apoptosis-related genes (Fas, BAX, and TP53) were upregulated acutely and for several days thereafter (days 1–3). In contrast, the expression of immune-modulatory (transcription factor 7, HLV-DOA, and CD6) and apoptosis inhibitory (c-myc, caspase 8, and Fas Ligand G) genes was downregulated initially and returned to normal with clinical recovery (days 7–10). These results indicate that the innate immune response, cytokine, and apoptosis pathways are upregulated acutely in uncomplicated malaria with concomitant downregulation of immune-modulatory and apoptosis inhibitory genes.

The combination of real-time PCR and capillary electrophoresis permits the rapid identification and quantification of pathogen genotypes., Simultaneous infection with multiple pathogens of the same species occurs with HIV, hepatitis C, Epstein-Barr virus, dengue, tuberculosis, and malaria. However, available methods do not distinguish among or quantify pathogen genotypes in individual patients; they also cannot test for novel insertions and deletions in genetically modified organisms. The strategy reported here accomplishes these goals with real-time polymerase chain reaction (PCR) and capillary electrophoresis. Real-time PCR with allotype-specific primers defines the allotypes (strains) present and the intensity of infection (copy number). Capillary electrophoresis defines the number of genotypes within each allotype and the intensity of infection by genotype. This strategy can be used to study the epidemiology of emerging infectious diseases with simultaneous infection by multiple genotypes, as demonstrated here with malaria. It also permits testing for insertions or deletions in genetically modified organisms that may be used for bioterrorism.

Objective.Acute hepatitis B virus (HBV) infections have been reported in long-term care facilities (LTCFs), primarily associated with infection control breaks during assisted blood glucose monitoring. We investigated HBV outbreaks that occurred in separate skilled nursing facilities (SNFs) to determine factors associated with transmission.Design.Outbreak investigation with case-control studies.Setting.Two SNFs (facilities A and B) in Durham, North Carolina, during 2009–2010.Patients.Residents with acute HBV infection and controls randomly selected from HBV-susceptible residents during the outbreak period.Methods.After initial cases were identified, screening was offered to all residents, with repeat testing 3 months later for HBV-susceptible residents. Molecular testing was performed to assess viral relatedness. Infection control practices were observed. Case-control studies were conducted to evaluate associations between exposures and acute HBV infection in each facility.Results.Six acute HBV cases were identified in each SNF. Viral phylogenetic analysis revealed a high degree of HBV relatedness within, but not between, facilities. No evaluated exposures were significantly associated with acute HBV infection in facility A; those associated with infection in facility B (all odds ratios >20) included injections, hospital or emergency room visits, and daily blood glucose monitoring. Observations revealed absence of trained infection control staff at facility A and suboptimal hand hygiene practices during blood glucose monitoring and insulin injections at facility B.Conclusions.These outbreaks underscore the vulnerability of LTCF residents to acute HBV infection, the importance of surveillance and prompt investigation of incident cases, and the need for improved infection control education to prevent transmission.

Background Malaria is the leading cause of death in Mozambique in children under five years old. In 2009, Mozambique developed a novel bed net distribution model to increase coverage, based on assumptions about sleeping patterns. The coverage and impact of a bed net distribution campaign using this model in four districts in Sofala Province, Mozambique was evaluated. Methods Paired household, cross-sectional surveys were conducted one month after the 2010 distribution of 140,000 bed nets and again 14 months after the campaign in 2011. During household visits, malaria blood smears were performed and haemoglobin levels were assessed on children under five and data on bed net ownership, access and use were collected; these indicators were analysed at individual, household and community levels. Logistic regression was used to evaluate predictors of malaria infection and anaemia. Results The campaign reached 98% (95% CI: 97-99%) of households registered during the precampaign listing, with 81% (95% CI: 77-85%) of sleeping spaces covered by campaign bed nets and 85% (95% CI: 81-88%) of the population sleeping in a sleeping space with a campaign bed net designated for the sleeping space. One year after the campaign, 65% (95% CI: 57-72%) of sleeping spaces were observed to have hanging bed nets. The proportion of sleeping spaces for which bed nets were reported used four or more times per week was 65% (95% CI: 56-74%) in the wet season and 60% (95% CI: 52-68%) in the dry season. Malaria parasitaemia prevalence in children under five years old was 47% (95% CI: 40-54%) in 2010 and 36% (95% CI: 27-45%) in 2011. Individual-level malaria infection and anaemia were significantly associated with community-level use of bed nets. Conclusions The campaign using the novel distribution model achieved high coverage, although usage was not uniformly high. A significant decrease in malaria parasitaemia prevalence a year after the campaign was not observed, but community-level use of bed nets was significantly associated with a reduced risk for malaria infection and anaemia in children under five. Electronic supplementary material The online version of this article (doi:10.1186/1475-2875-13-427) contains supplementary material, which is available to authorized users.