Modeling household transmission dynamics: Application to waterborne diarrheal disease in Central Africa.

INTRODUCTION:We describe a method for analyzing the within-household network dynamics of a disease transmission. We apply it to analyze the occurrences of endemic diarrheal disease in Cameroon, Central Africa based on observational, cross-sectional data available from household health surveys. METHODS:To analyze the data, we apply formalism of the dynamic SID (susceptible-infected-diseased) process that describes the disease steady-state while adjusting for the household age-structure and environment contamination, such as water contamination. The SID transmission rates are estimated via MCMC method with the help of the so-called synthetic likelihood approach. RESULTS:The SID model is fitted to a dataset on diarrhea occurrence from 63 households in Cameroon. We show that the model allows for quantification of the effects of drinking water contamination on both transmission and recovery rates for household diarrheal disease occurrence as well as for estimation of the rate of silent (unobserved) infections. CONCLUSIONS:The new estimation method appears capable of genuinely capturing the complex dynamics of disease transmission across various human, animal and environmental compartments at the household level. Our approach is quite general and can be used in other epidemiological settings where it is desirable to fit transmission rates using cross-sectional data. SOFTWARE SHARING:The R-scripts for carrying out the computational analysis described in the paper are available at https://github.com/cbskust/SID

Impact of Covid-19 on risk of severe maternal morbidity

Abstract Background We examined the risk of severe life-threatening morbidity in pregnant patients with Covid-19 infection. Methods We conducted a population-based study of 162,576 pregnancies between March 2020 and March 2022 in Quebec, Canada. The main exposure was Covid-19 infection, including the severity, period of infection (antepartum, peripartum), and circulating variant (wildtype, alpha, delta, omicron). The outcome was severe maternal morbidity during pregnancy up to 42 days postpartum. We estimated risk ratios (RR) and 95% confidence intervals (CI) for the association between Covid-19 infection and severe maternal morbidity using adjusted log-binomial regression models. Results Covid-19 infection was associated with twice the risk of severe maternal morbidity compared with no infection (RR 2.02, 95% CI 1.76–2.31). Risks were elevated for acute renal failure (RR 3.01, 95% CI 1.79–5.06), embolism, shock, sepsis, and disseminated intravascular coagulation (RR 1.35, 95% CI 0.95–1.93), and severe hemorrhage (RR 1.49, 95% CI 1.09–2.04). Severe antepartum (RR 13.60, 95% CI 10.72–17.26) and peripartum infections (RR 20.93, 95% CI 17.11–25.60) were strongly associated with severe maternal morbidity. Mild antepartum infections also increased the risk, but to a lesser magnitude (RR 3.43, 95% CI 2.42–4.86). Risk of severe maternal morbidity was around 3 times greater during circulation of wildtype and the alpha and delta variants, but only 1.2 times greater during omicron. Conclusions Covid-19 infection during pregnancy increases risk of life-threatening maternal morbidity, including renal, embolic, and hemorrhagic complications. Severe Covid-19 infection with any variant in the antepartum or peripartum periods all increase the risk of severe maternal morbidity

Muddying the Waters: A New Area of Concern for Drinking Water Contamination in Cameroon

In urban Maroua, Cameroon, improved drinking water sources are available to a large majority of the population, yet this water is frequently distributed through informal distribution systems and stored in home containers (canaries), leaving it vulnerable to contamination. We assessed where contamination occurs within the distribution system, determined potential sources of environmental contamination, and investigated potential pathogens. Gastrointestinal health status (785 individuals) was collected via health surveys. Drinking water samples were collected from drinking water sources and canaries. Escherichia coli and total coliform levels were evaluated and molecular detection was performed to measure human-associated faecal marker, HF183; tetracycline-resistance gene, tetQ; Campylobacter spp.; and Staphylococcus aureus. Statistical analyses were performed to evaluate the relationship between microbial contamination and gastrointestinal illness. Canari samples had higher levels of contamination than source samples. HF183 and tetQ were detected in home and source samples. An inverse relationship was found between tetQ and E. coli. Presence of tetQ with lower E. coli levels increased the odds of reported diarrhoeal illness than E. coli levels alone. Further work is warranted to better assess the relationship between antimicrobial-resistant bacteria and other pathogens in micro-ecosystems within canaries and this relationship’s impact on drinking water quality

Practicing international

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