Impact Of Control Measures Research Articles

CO2 flux emissions at two urban sites in Beijing and responses to human activity

During the COVID-19 pandemic in 2020–2021, continuous measurements of CO2 flux were conducted using the eddy covariance method at two representative urban sites in Beijing, China, to assess the temporal and spatial variability of CO2 emissions in urban areas. We further examined the impacts of vegetation and human activities on CO2 emissions. Both sites exhibited characteristics of urban carbon sources in the two years, with higher carbon emissions observed at the Beijing Academy of Landscape and Greening Science (BALGS) site compared to that in the campus of the Research Center of Eco-Environment (RCEES), Chinese Academy of Science. Although the seasonal and diurnal patterns of CO2 flux were similar at both sites, differences in the magnitude of CO2 flux emissions were primarily attributed to variations in underlying surface characteristics within the source area. Seasonal variations and daytime carbon uptake reflected the role of urban vegetation in carbon sequestration. Additionally, our observations revealed that the implementation of COVID-19 control measures effectively reduced urban carbon emissions, with stricter controls associated with lower carbon emissions. Furthermore, we compared the differences in carbon emission reductions between anthropogenic controls and seasonal variations at the two sites. We found that at the densely trafficked BALGS site, the impact of control measures on carbon emission reductions was more pronounced, while at the RCEES site, seasonal variations contributed more to carbon uptake compared to control measures.

Global dynamics of a periodic brucellosis model with time delay and environmental factors

In China, brucellosis has always been a significant public health issue, especially in the pastoral regions of northern provinces where animal husbandry is well-developed. However, the impact of control measures, breeding characteristics and temperature fluctuations on the transmission dynamics of brucellosis outbreaks remains unclear. We construct a periodic mechanism-driven dynamic model with latent delay coupled with the regional breeding and temperature characteristics of Xinjiang Region. Theoretically, the global dynamics of periodic solutions are demonstrated by the theory of monotone dynamical system. In the application, the monthly human brucellosis cases and average temperature data of Xinjiang from 2015 to 2020 are fitted, and the basic reproduction number of brucellosis transmission is evaluated as 0.6691. Nonetheless, it is yet unable to attain the national control standards in the short term. The findings suggest that: 1. Interactions of periodic fluctuations in Brucella survival time and sheep shearing are key factors leading to the periodic outbreaks of brucellosis. 2. Improving the frequency of environmental disinfection could quickly eliminate the brucellosis epidemic. Specifically, when the disinfection frequency was once a month, the national control standard could be reached 5 years ahead of schedule. 3. In extreme cases, when the immunization rate κ=0 or the detection rate γ=0, the basic reproduction number might still be less than 1. From an epidemiological perspective, non-immunization control measures may be implemented with the reduction of brucellosis cases. The aforementioned statement may also bear resemblance to the preventive and control measures implemented in our country.

Evaluation of the DN-Mini (miniaturized double net) trap for sampling host-seeking Anopheles mosquitoes in malaria-endemic villages of southern Tanzania.

Surveillance of malaria vectors is crucial for assessing the transmission risk and impact of control measures. Human landing catches (HLC) directly estimate the biting rates but raise ethical concerns due to the exposure of volunteers to mosquito-borne pathogens. A common alternative is the CDC-light trap, which is effective for catching host-seeking mosquitoes indoors but not outdoors. New, exposure-free methods are needed for sampling mosquitoes indoors and outdoors in ways that reflect their natural risk profiles. The aim of this study was therefore to evaluate the efficacy of the miniaturized double net trap (DN-Mini) for sampling host-seeking mosquitoes in south-eastern Tanzania, where malaria transmission is dominated by Anopheles funestus. Adult mosquitoes were collected from 222 randomly selected houses across three villages (74 per village) in Ulanga district, south-eastern Tanzania, using the DN-Mini traps, CDC-Light traps, and Prokopack aspirators. First, we compared CDC-light and DN-Mini traps for collecting indoor host-seeking mosquitoes, while Prokopack aspirators were used for indoor-resting mosquitoes. Second, we deployed the DN-Mini and Prokopack aspirators to collect host-seeking and resting mosquitoes indoors and outdoors. Generalized linear mixed models (GLMM) with a negative binomial distribution were used to compare the effectiveness of the traps for catching different mosquito species. The DN-Mini was 1.53 times more efficient in collecting An. funestus indoors (RR = 1.53, 95% CI: 1.190-1.98) compared to the CDC-Light trap. However, for Anopheles arabiensis, the DN-Mini caught only 0.32 times as many mosquitoes indoors as the CDC-Light traps (RR = 0.32, 95% CI: 0.183-0.567). Both An. funestus and An. arabiensis were found to be more abundant indoors than outdoors when collected using the DN-Mini trap. Similarly, the Prokopack aspirator was greater indoors than outdoors for both An. funestus and An. arabiensis. The DN-Mini outperformed the CDC-light trap in sampling the dominant malaria vector, An. funestus species, but was less effective in capturing An. arabiensis, and for both vector species, the biting risk was greater indoors than outdoors when measured using the DN-Mini trap. These findings highlight the importance of selecting appropriate trapping methods based on mosquito species and behaviors.

The 2021 Cholera Outbreak in Nigeria, Data and Models Used to Explore Controls and Challenges

Cholera is an acute diarrhoeal illness that affects humanity globally, especially in areas where there is limited access to clean water and adequate sanitation. A Nigerian cholera outbreak from January 2021 to January 2022 resulted in many cases and deaths. A mathematical model that takes into consideration the challenges that affected effective implementation of control measures for this 2021 cholera outbreak is developed. Important epidemiological features of the model such as the basic reproduction number (R0), the disease-free equilibrium, and the endemic equilibrium are determined and analysed. The disease-free equilibrium is shown to be asymptotically stable provided R0 < 1. The model is shown to undergo forward bifurcation at R0 = 1 using the Centre Manifold Theorem. Sensitivity analysis is used to determine the parameters that have the highest influence on transmission. Fitting the model to data from the 2021 Nigerian cholera outbreak, important parameters of the model are estimated. The impact of control measures as well as challenges that affected the effective implementation of these control measures are considered.

Measles virus transmission patterns and public health responses during Operation Allies Welcome: a descriptive epidemiological study

On Aug 29, 2021, Operation Allies Welcome (OAW) was established to support the resettlement of more than 80 000 Afghan evacuees in the USA. After identification of measles among evacuees, incoming evacuee flights were temporarily paused, and mass measles vaccination of evacuees aged 6 months or older was introduced domestically and overseas, with a 21-day quarantine period after vaccination. We aimed to evaluate patterns of measles virus transmission during this outbreak and the impact of control measures. We conducted a measles outbreak investigation among Afghan evacuees who were resettled in the USA as part of OAW. Patients with measles were defined as individuals with an acute febrile rash illness between Aug 29, 2021, and Nov 26, 2021, and either laboratory confirmation of infection or epidemiological link to a patient with measles with laboratory confirmation. We analysed the demographics and clinical characteristics of patients with measles and used epidemiological information and whole-genome sequencing to track transmission pathways. A transmission model was used to evaluate the effects of vaccination and other interventions. 47 people with measles (attack rate: 0·65 per 1000 evacuees) were reported in six US locations housing evacuees in four states. The median age of patients was 1 year (range 0-26); 33 (70%) were younger than 5 years. The age distribution shifted during the outbreak towards infants younger than 12 months. 20 (43%) patients with wild-type measles virus had rash onset after vaccination. No fatalities or community spread were identified, nor further importations after flight resumption. In a non-intervention scenario, transmission models estimated that a median of 5506 cases (IQR 10-5626) could have occurred. Infection clusters based on epidemiological criteria could be delineated into smaller clusters using phylogenetic analyses; however, sequences with few substitution count differences did not always indicate single lines of transmission. Implementation of control measures limited measles transmission during OAW. Our findings highlight the importance of integration between epidemiological and genetic information in discerning between individual lines of transmission in an elimination setting. US Centers for Disease Control and Prevention.

Qualitative Analysis of the Transmission Dynamics and Optimal Control of Covid-19

Globally, the COVID-19 presents a serious concern to the wellbeing of people. COVID-19 was first detected in Wuhan, China. The disease became a source of concern for Nigerians after the country registered its first case in February 2020. Currently, the country has recorded 255,103 confirmed cases, 249,246 recovered cases, and 3,142 deaths as of March 21, 2022. We proposed a SEQIHRV model to investigate the spread of coronavirus disease in Nigeria. This model defines the infection dynamics' transmission routes as well as effect of contaminated surfaces on the human population. Unfortunately, the virus's propagation and mortality from COVID-19 is increasing daily. Therefore, it is required to manage and control the flow of the infection. The impact of control measures as time-dependent interventions was investigated in this study utilizing optimization technique to determine their effects on the spread of Corona virus. The basic reproduction was calculated and used to calcite the sensitive parameters affecting the system, which revealed the key parameters leading to COVID-19 propagation. The control optimization of the sytem was performed using Pontryagin's maximum principle to determine the best approach for controlling the spread. The discoveries from the simulation showed that the combination of all four control approaches will help to reduce infection to zero in the population.

Using Data of a Lassa Fever Epidemic in Nigeria: A Mathematical Model Is Shown to Capture the Dynamics and Point to Possible Control Methods

Lassa fever is a deadly viral illness that is endemic in some parts of West Africa, including Nigeria. A deterministic model in the form of a non-linear system of differential equations is developed to analyse the dynamics and possible control of the disease. The model is tested by fitting it to data from Nigeria’s Lassa fever outbreak using a least-squares fitting routine and the model is shown to provide a reasonable fit to the data. Parameters representing various control measures in the model are estimated using the model fitting. Important epidemiological features of the model such as the basic reproduction number (R0), the disease-free equilibrium, and the endemic equilibrium are determined and analysed. The disease-free equilibrium is shown to be asymptotically stable when R0<1. A bifurcation about R0=1 was determined using the Center Manifold Theorem. Using numerical simulations of the model future dynamics of Lassa fever disease in Nigeria are predicted and the impact of control measures on the disease determined. The use of approved rodenticides is shown to be the most effective control followed by reducing person-to-person and rodent-to-person contacts, respectively. Isolation and treatment of infected individuals are shown to be less effective when compared with the other control measures.

The World Health Organization COVID-19 surveillance database

In January 2020, SARS-CoV-2 virus was identified as a cause of an outbreak in China. The disease quickly spread worldwide, and the World Health Organization (WHO) declared the pandemic in March 2020.From the first notifications of spread of the disease, the WHO’s Emergency Programme implemented a global COVID-19 surveillance system in coordination with all WHO regional offices. The system aimed to monitor the spread of the epidemic over countries and across population groups, severity of the disease and risk factors, and the impact of control measures. COVID-19 surveillance data reported to WHO is a combination of case-based data and weekly aggregated data, focusing on a minimum global dataset for cases and deaths including disaggregation by age, sex, occupation as a Health Care Worker, as well as number of cases tested, and number of cases newly admitted for hospitalization. These disaggregations aim to monitor inequities in COVID-19 distribution and risk factors among population groups.SARS-CoV-2 epidemic waves continue to sweep the world; as of March 2022, over 445 million cases and 6 million deaths have been reported worldwide. Of these, over 327 million cases (74%) have been reported in the WHO surveillance database, of which 255 million cases (57%) are disaggregated by age and sex. A public dashboard has been made available to visualize trends, age distributions, sex ratios, along with testing and hospitalization rates. It includes a feature to download the underlying dataset.This paper will describe the data flows, database, and frontend public dashboard, as well as the challenges experienced in data acquisition, curation and compilation and the lessons learnt in overcoming these. Two years after the pandemic was declared, COVID-19 continues to spread and is still considered a Public Health Emergency of International Concern (PHEIC). While WHO regional and country offices have demonstrated tremendous adaptability and commitment to process COVID-19 surveillance data, lessons learnt from this major event will serve to enhance capacity and preparedness at every level, as well as institutional empowerment that may lead to greater sharing of public health evidence during a PHEIC, with a focus on equity.

Scientific Findings of the Southern and Central Africa International Center of Excellence for Malaria Research: Ten Years of Malaria Control Impact Assessments in Hypo-, Meso-, and Holoendemic Transmission Zones in Zambia and Zimbabwe.

For a decade, the Southern and Central Africa International Center of Excellence for Malaria Research has operated with local partners across study sites in Zambia and Zimbabwe that range from hypo- to holoendemic and vary ecologically and entomologically. The burden of malaria and the impact of control measures were assessed in longitudinal cohorts, cross-sectional surveys, passive and reactive case detection, and other observational designs that incorporated multidisciplinary scientific approaches: classical epidemiology, geospatial science, serosurveillance, parasite and mosquito genetics, and vector bionomics. Findings to date have helped elaborate the patterns and possible causes of sustained low-to-moderate transmission in southern Zambia and eastern Zimbabwe and recalcitrant high transmission and fatality in northern Zambia. Cryptic and novel mosquito vectors, asymptomatic parasite reservoirs in older children, residual parasitemia and gametocytemia after treatment, indoor residual spraying timed dyssynchronously to vector abundance, and stockouts of essential malaria commodities, all in the context of intractable rural poverty, appear to explain the persistent malaria burden despite current interventions. Ongoing studies of high-resolution transmission chains, parasite population structures, long-term malaria periodicity, and molecular entomology are further helping to lay new avenues for malaria control in southern and central Africa and similar settings.

COVID-19 as a social disease: qualitative analysis of COVID-19 prevention needs, impact of control measures and community responses among racialized/ethnic minorities in Antwerp, Belgium

BackgroundIn high income countries, racialized/ethnic minorities are disproportionally affected by COVID-19. Despite the established importance of community involvement in epidemic preparedness, we lack in-depth understanding of these communities’ experiences with and responses to COVID-19. We explored information and prevention needs, coping mechanisms with COVID-19 control measures and their impact on lived experiences among selected racialized/ethnic minority communities.MethodsThis qualitative rapid assessment conducted in Antwerp/Belgium used an interpretative and participatory approach. We included migrant communities with geographic origins ranging from Sub-Saharan Africa, North-Africa to the Middle East, Orthodox Jewish communities and professional community workers. Data were collected between May 2020–May 2021 through key informant-, in-depth interviews and group discussions (N = 71). Transcripts were analyzed inductively, adopting a reflexive thematic approach. A community advisory board provided feedback throughout the research process.ResultsParticipants indicated the need for tailored information in terms of language and timing. At the start of the epidemic, they perceived official public health messages as insufficient to reach all community members. Information sources included non-mainstream (social) media and media from home countries, hampering a nuanced understanding of virus transmission mechanisms and local and national protection measures. Participants felt the measures’ most negative impact on their livelihoods (e.g. loss of income, disruption of social and immigration support). Economic insecurity triggered chronic stress and fears at individual and family level. High degrees of distrust in authorities and anticipated stigma were grounded in previously experienced racial and ethnic discrimination. Community-based initiatives mitigated this impact, ranging from disseminating translated and tailored information, providing individual support, and successfully reaching community members with complex needs (e.g. the elderly, digitally illiterate people, those with small social networks or irregular legal status).ConclusionStudy participants’ narratives showed how coping with and responding to COVID-19 was strongly intertwined with socio-economic and ethnic/racial characteristics. This justifies conceptualizing COVID-19 a social disease. At the same time, communities demonstrated resilience in responding to these structural vulnerabilities. From a health equity perspective, we provide concrete policy recommendations grounded in insights into communities’ structural vulnerabilities and resilience.

Social Contacts and Transmission of COVID-19 in British Columbia, Canada.

BackgroundClose-contact rates are thought to be a driving force behind the transmission of many infectious respiratory diseases. Yet, contact rates and their relation to transmission and the impact of control measures, are seldom quantified. We quantify the response of contact rates, reported cases and transmission of COVID-19, to public health contact-restriction orders, and examine the associations among these three variables in the province of British Columbia, Canada.MethodsWe derived time series data for contact rates, daily cases and transmission of COVID-19 from a social contacts survey, reported case counts and by fitting a transmission model to reported cases, respectively. We used segmented regression to investigate impacts of public health orders; Pearson correlation to determine associations between contact rates and transmission; and vector autoregressive modeling to quantify lagged associations between contacts rates, daily cases, and transmission.ResultsDeclines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in cases showed a reporting delay of about 2 weeks. Contact rates were a significant driver of COVID-19 and explained roughly 19 and 20% of the variation in new cases and transmission, respectively. Interestingly, increases in COVID-19 transmission and cases were followed by reduced contact rates: overall, daily cases explained about 10% of the variation in subsequent contact rates.ConclusionWe showed that close-contact rates were a significant time-series driver of transmission and ultimately of reported cases of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest possible behavioral feedback, by which increased reported cases lead to reduced subsequent contact rates. Our findings help to explain and validate the commonly assumed, but rarely measured, response of close contact rates to public health guidelines and their impact on the dynamics of infectious diseases.

Empirical Modeling of COVID-19 Evolution with High/Direct Impact on Public Health and Risk Assessment.

This report develops a conceivable mathematical model for the transmission and spread of COVID-19 in Romania. Understanding the early spread dynamics of the infection and evaluating the effectiveness of control measures in the first wave of infection is crucial for assessing and evaluating the potential for sustained transmission occurring in the second wave. The main aim of the study was to emphasize the impact of control measures and the rate of case detection in slowing the spread of the disease. Non pharmaceutical control interventions include government actions, public reactions, and other measures. The methodology consists of an empirical model, taking into consideration the generic framework of the Stockholm Environment Institute (SEI) Epidemic–Macroeconomic Model, and incorporates the effect of interventions through a multivalued parameter, a stepwise constant varying during different phases of the interventions designed to capture their impact on the model. The model is mathematically consistent and presents various simulation results using best-estimated parameter values. The model can be easily updated later in response to real-world alterations, for example, the easing of restrictions. We hope that our simulation results may guide local authorities to make timely, correct decisions for public health and risk assessment.

Factors influencing SARS-CoV-2 transmission and outbreak control measures in densely populated settings

Starting with a handful of SARS-CoV-2 infections in dormitory residents in late March 2020, rapid transmission in their dense living environments ensued and by October 2020, more than 50,000 acute infections were identified across various dormitories in Singapore. The aim of the study is to identify combination of factors facilitating SARS-CoV-2 transmission and the impact of control measures in a dormitory through extensive epidemiological, serological and phylogenetic investigations, supported by simulation models. Our findings showed that asymptomatic cases and symptomatic cases who did not seek medical attention were major drivers of the outbreak. Furthermore, each resident had about 30 close contacts and each infected resident spread to 4.4 (IQR 3.5–5.3) others at the start of the outbreak. The final attack rate of the current outbreak was 76.2% (IQR 70.6–98.0%) and could be reduced by further 10% under a modified dormitory housing condition. These findings are important when designing living environments in a post COVID-19 future to reduce disease spread and facilitate rapid implementation of outbreak control measures.

Estimated Dissemination Ratio-A Practical Alternative to the Reproduction Number for Infectious Diseases.

Policymakers require consistent and accessible tools to monitor the progress of an epidemic and the impact of control measures in real time. One such measure is the Estimated Dissemination Ratio (EDR), a straightforward, easily replicable, and robust measure of the trajectory of an outbreak that has been used for many years in the control of infectious disease in livestock. It is simple to calculate and explain. Its calculation and use are discussed below together with examples from the current COVID-19 outbreak in the UK. These applications illustrate that EDR can demonstrate changes in transmission rate before they may be clear from the epidemic curve. Thus, EDR can provide an early warning that an epidemic is resuming growth, allowing earlier intervention. A conceptual comparison between EDR and the commonly used reproduction number is also provided.

The Impact of Control Measures and Holiday Seasons on Incidence and Mortality Rate of COVID-19 in Iran

Background: Preventive measures on the COVID-19 pandemic is an effective way to control its spread. We aimed to investigate the effect of control measures and holiday seasons on the incidence and mortality rate of COVID-19 in Iran. Study design: An observational study. Methods: The daily data of confirmed new cases and deaths in Iran were taken from the Johns Hopkins University COVID-19 database. We calculated weekly data from 19 Feb to 6 Oct 2020. To estimate the impact of control measures and holiday seasons on the incidence rate of new cases and deaths, an autoregressive hidden Markov model (ARHMM) with two hidden states fitted the data. The hidden states of the fitted model can distinguish the peak period from the non-peak period. Results: The control measures with a delay of one-week and two-week had a decreasing effect on the new cases in the peak and non-peak periods, respectively (P=0.005). The holiday season with a two-week delay increased the total number of new cases in the peak periods (P=0.031). The peak period for the occurrence of COVID-19 was estimated at 3 weeks. In the peak period of mortality, the control measures with a three-week delay decreased the COVID-19 mortality (P=0.010). The expected duration of staying in the peak period of mortality was around 6 weeks. Conclusions: When an increasing trend was seen in the country, the control measures could decline the incidence and mortality related to COVID-19. Implementation of official restrictions on holiday seasons could prevent an upward trend of incidence for COVID-19 during the peak period.

Estimation of Rift Valley fever virus spillover to humans during the Mayotte 2018–2019 epidemic

Rift Valley fever (RVF) is an emerging, zoonotic, arboviral hemorrhagic fever threatening livestock and humans mainly in Africa. RVF is of global concern, having expanded its geographical range over the last decades. The impact of control measures on epidemic dynamics using empirical data has not been assessed. Here, we fitted a mathematical model to seroprevalence livestock and human RVF case data from the 2018-2019 epidemic in Mayotte to estimate viral transmission among livestock, and spillover from livestock to humans through both direct contact and vector-mediated routes. Model simulations were used to assess the impact of vaccination on reducing the epidemic size. The rate of spillover by direct contact was about twice as high as vector transmission. Assuming 30% of the population were farmers, each transmission route contributed to 45% and 55% of the number of human infections, respectively. Reactive vaccination immunizing 20% of the livestock population reduced the number of human cases by 30%. Vaccinating 1 mo later required using 50% more vaccine doses for a similar reduction. Vaccinating only farmers required 10 times as more vaccine doses for a similar reduction in human cases. Finally, with 52.0% (95% credible interval [CrI] [42.9-59.4]) of livestock immune at the end of the epidemic wave, viral reemergence in the next rainy season (2019-2020) is unlikely. Coordinated human and animal health surveillance, and timely livestock vaccination appear to be key to controlling RVF in this setting. We furthermore demonstrate the value of a One Health quantitative approach to surveillance and control of zoonotic infectious diseases.

The most effective interventions

Coronavirus By 23 January 2020, China had imposed a national emergency response to restrict travel and impose social distancing measures on its populace in an attempt to inhibit the transmission of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2). However, which measures were most effective is uncertain. Tian et al. performed a quantitative analysis of the impact of control measures between 31 December 2019 and 19 February 2020, which encompasses the Lunar New Year period when millions of people traveled across China for family visits. Travel restrictions in and out of Wuhan were too late to prevent the spread of the virus to 262 cities within 28 days. However, the epidemic peaked in Hubei province on 4 February 2020, indicating that measures such as closing citywide public transport and entertainment venues and banning public gatherings combined to avert hundreds of thousands of cases of infection. It is unlikely that this decline happened because the supply of susceptible people was exhausted, so relaxing control measures could lead to a resurgence. Science , this issue p. [638][1] [1]: /lookup/doi/10.1126/science.abb6105

Impact of control measures and typhoon weather on characteristics and formation of PM2.5 during the 2016 G20 summit in China

The implementation of strict emission control during the G20 summit in China and the occurrence of Typhoon Malarkas in September 2016 provided a valuable opportunity to examine the role of control measures and special weather condition in the formation of PM2.5. Water-soluble inorganic ions (WSII) were measured hourly in addition to PM2.5 mass concentration and black carbon (BC) and gaseous pollutants in Ningbo located in the Yangtze River Delta (YRD) region of China. Three distinct cases, i.e., a control case, a normal case, and a typhoon case, were investigated during the study period. PM2.5 was higher in the control case (37.5 μg m−3) than in the normal case (29.8 μg m−3), whereas the lowest PM2.5 (14.2 μg m−3) was observed in the typhoon case. The analyses of meteorology and backward trajectory suggested that stable weather and regional transport from inland regions accounted for the high PM2.5 under strict control. Only the concentrations of Ca2+ and NO3− decreased in the control case, while those of all water-soluble inorganic components (except Na+ and Mg2+) decreased substantially in the typhoon case. SO42− dominated the WSII, with the highest contribution, 62%, in the control case. This result was attributed to a stagnant atmosphere with a high relative humidity (RH), which was beneficial for the transformation of SO2 to SO42−. The control and typhoon cases both resulted in extremely low NO2, but the contribution of NO3− to PM2.5 was reduced in the control case and increased in the typhoon case. The close correlation of the NOR (nitrate oxidation ratio) with Na+ and Mg2+ in the typhoon case was indicative of sea salt associated with the typhoon which provided a surface for the heterogeneous formation of NO3−. The presented results facilitate a better understanding of the characteristics and formation of PM2.5 under the influence of artificial control and natural intervention.

Modelling the reproductive power function

ABSTRACT This paper discusses methods of estimating the reproductive power and the accompanying survival function of communicable events, e.g. infectious disease transmission. The early stage of an outbreak can be described by the infectiousness of the outbreak process, but in later stages of the outbreak, this is complicated by factors such as changing contact patterns and the impact of control measures. It is important to take these factors into account in order to get a good, if approximate, model for an outbreak process. This paper proposes a non-homogeneous birth process and regression model for the reproductive power function, similar to models in discrete survival analysis. A baseline reproductive power function gives a description of the outbreak when covariates are at their baseline values. As an illustration these methods are applied to an avian influenza (H5N1) outbreak among poultry in Thailand.

Insights from quantitative and mathematical modelling on the proposed WHO 2030 goal for schistosomiasis.

Schistosomiasis remains one of the neglected tropical diseases (NTDs) impacting millions of people around the world. The World Health Organization (WHO) recently proposed a goal of elimination as a public health problem (EPHP) for schistosomiasis to be reached by 2030. Current WHO treatment guidelines for achieving EPHP focus on targeting school-aged children. The NTD Modelling Consortium has developed mathematical models to study schistosomiasis transmission dynamics and the impact of control measures. Our modelling insights on Schistosoma mansoni have shown that EPHP is likely to be attainable in low to moderate prevalence settings using the current guidelines. However, as prevalence rises within high prevalence settings, EPHP is less likely to be achieved unless both school-aged children and adults are treated (with coverage levels increasing with the adult burden of infection). We highlight the challenges that are faced by treatment programmes, such as non-adherence to treatment and resurgence, which can hinder progress towards achieving and maintaining EPHP. Additionally, even though EPHP may be reached, prevalence can still be high due to persisting infections. Therefore, without interruption of transmission, treatment will likely have to continue to maintain EPHP. Further modelling work is being carried out, including extending our results to S. haematobium. By providing these modelling insights, we aim to inform discussions on the goals and treatment guidelines for schistosomiasis.